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On 18 April 2018, Venetia Karamitsou, PhD student in the Disease Dynamics group at the University of Cambridge, held a talk at SACEMA on modelling the evolution of influence.

According to the WHO, there are 3 to 5 million cases of severe influenza infections per year, and 250-500,000 deaths per year, primarily among high-risk groups, which in industrialized countries are mainly the people over 65 and people with chronic illnesses. There is no treatment for influenza; there are antivirals, but these have risks associated with their use, so are mainly reserved for life-threatening cases. Thus, vaccination remains the most effective way of dealing with influenza. Given the importance of vaccination, it is worrisome that influenza mutates often, making reinfection possible even for vaccinated individuals.

Existing models regarding the evolution of influenza focus on either changes within hosts or between hosts. Between-host or population level models study how influenza spreads among many different individuals in a population. The prototypical example of such a model is the SIR model, which keeps track of the susceptible, infected and recovered individuals from the onset of an epidemic until its end. The within-host models study how influenza behaves inside one particular host. They keep track of target cells, which the virus can enter and turn into infected cells. These infected cells then start releasing more virus until they die, either due to damage from the virus within them or due to the actions of the immune system. So within-host models track, at their most basic level, the number of target cells, infected cells and virions inside an individual. Finally, influenza is a rapidly mutating virus, which means that as it keeps accumulating mutations in its genome, it becomes so different that our immune system barely recognizes it anymore even if we have already been infected with it in the past. This evolution is referred to as the antigenic drift of influenza, and it is one mechanism by which the virus can keep re-infecting individuals.

The main motivation behind Venetia’s research is to find out how we can combine both types of models, the within and between hosts models, into one. From her simulations it became clear that when you have one strong and one weak strain spreading inside a host, it could be (although counterintuitively) that the weak strain ends up becoming more prevalent in the whole population. The reason being that if you introduce a vaccine that targets specifically the strong strain, then the weak one may end up dominating the host. In that case the weak strain will be transmitted to someone else. If the same happens with other individuals in the population, it will be the weak strain that ends up more prevalent in the population.

Considering that vaccination is the main control strategy against influenza outbreaks, these results can be useful in reassessing vaccination policies to ensure both a low disease incidence rate as well as a decrease in antigenic drift speed of influenza.

I was born in Caracas, Venezuela, to a mother from Kansas City, Missouri and a Venezuelan father with German roots. Growing up, I watched my parents navigate, negotiate and resolve vast cultural differences that challenged their worldviews every day. For several years, we lived with my grandparents, who co-founded the Foundation for the Conservation of Nature (FUDENA), Venezuela’s major conservation NGO. My grandfather managed a cattle ranch and biological research station that has given rise to more than 500 peer-reviewed publications and dissertation projects conducted by Venezuelan and international students of ecology, animal behaviour and animal husbandry.

At home in Caracas, we had three large artificial ponds with pet turtles and Orinoco crocodiles, and three fenced areas with capuchin monkeys and other animals that were sometimes brought from the ranch for veterinary examinations or because they could no longer survive in the wild. I grew up with a sense that all creatures have realities of their own, many of which I would spend my life trying to understand. I’ve known for as long as I can remember that I would pursue a career in biology. In recent years, I have discovered that my love for biology – and for science – is inextricably tied to my love for my home country, whose rich tropical wealth is being eclipsed by its oil wealth and corruption. What has taken me by surprise is that I would someday be studying viruses, which aren’t quite alive, and that I would be finding these viruses in the rubble of an unprecedented public health crisis in Venezuela.

Arthropod-borne viruses in Latin America

In Latin America, arthropod-borne viruses (arboviruses) such as Dengue, Chikungunya, Yellow Fever, West Nile, Zika and Mayaro viruses are becoming increasingly widespread (1). Clinical symptoms of these diseases range from mild febrile illness to haemorrhagic fever, neuroinvasive disease, and death. Substantial international efforts have been made to monitor and control the spread of arboviruses in Latin America. From the 1950s to the 1980s, Venezuela was a leading example in the surveillance and control of arboviruses. However, in recent years, the country’s public health system collapsed amid social, political and economic turmoil. Conducting arbovirus surveillance and control in the country has become increasingly challenging, yet the need for effective interventions is greater than ever.

International collaboration for arbovirus surveillance in Venezuela

During my graduate studies at the University of Florida (UF), I was given the opportunity to study arboviruses in Venezuela. I embraced the opportunity to participate in this project, knowing that the circumstances were going to be challenging. The collaborative project was initiated by myself together with Dr. Glenn Morris, Jr., director of the UF Emerging Pathogens Institute (EPI), Dr. John Lednicky, a virologist at the UF Dept of Environmental and Global Health of the College of Public Health and Health Professions and EPI, Dr. Juliet Pulliam (then at the UF Department of Biology and EPI), and Dr. Alberto Paniz-Mondolfi, who at that time was practicing medicine at the Hospital Internacional Barquisimeto in Cabudare, Venezuela (now at Instituto Diagnóstico Barquisimeto). This project was designed to monitor the spread of arboviruses across international borders: Venezuela and the United States are in close proximity, and there is a substantial degree of travel from Venezuela to my resident state of Florida. Our project was funded by a National Science Foundation grant (PI: Juliet Pulliam) and by private donors through a crowdfunding campaign.

Differential diagnosis of arboviruses is required

In early 2016, during the start of our project, Brazil was reporting an increase in microcephaly and Guillain-Barré syndrome. This trend was associated with the spread of a virus that was relatively new to the Americas: Zika virus(ZIKV), the causative agent of Zika fever (ZF). One aim of our study was to establish the occurrence of ZIKV in Barquisimeto, Venezuela, as no laboratory-confirmed information was available at the time. This information would be useful for physicians trying to diagnose arbovirus infections in areas where dengue- and chikungunya viruses co-circulate endemically. Noteworthy, the clinical symptoms of ZF – mild fever, conjunctivitis, maculopapular rash, and arthralgias – resemble those of other arboviruses. Thus, as for other arbovirus infections, clinical diagnosis alone cannot be relied on to diagnose ZF. Because ZIKV can interfere with foetal development and can cause a range of congenital problems that include microcephaly and delayed neuromuscular development, differential diagnosis of ZF and detection of ZIKV infections in otherwise asymptomatic patients is essential, especially for women who are pregnant. Diagnosis of suspected ZIKV infections is most accurate (“gold standard”) when the virus is isolated from the patients, but is typically attempted using some type of ZIKV nucleic acid detection test, such as by using by reverse-transcription polymerase chain reaction (RT-PCR). Evidence of ZIKV infection is also attained through serology (detection of specific IgM antibodies as evidence for new infection and serum IgG for convalescence or previous exposure). However, serology tests have been shown to be problematic for patients who live in areas endemic for viruses related to ZIKV, because the antibodies against the viruses can be cross-reactive; this results in frequent false-positive test results.

Challenges posed by Venezuela’s complex social and political landscape

In Venezuela, by 2016, most diagnostic laboratories and pharmaceutical companies had gone bankrupt and were no longer operational. Publication of Venezuela’s epidemiological bulletin had ceased. Unfortunately, access to basic medical supplies, equipment and reagents for diagnosis of viral diseases was extremely limited. The country’s healthcare system was overburdened and under-resourced. In February of 2016, at the UF EPI, we prepared specimen collection boxes containing blood collection tubes, syringes, cryovials and other basic supplies to provide diagnostic support and to track the virus during this time of need.

I was able to solicit help from local friends and family to transport supplies from Caracas, the capital, to Barquisimeto, a city that is four hours away. Upon arrival to the hospital, we were greeted by a deluge of doctors, patients and interns who had observed symptoms of ZF but were unsure of whether the virus was indeed in Venezuela. Reports of ZF in neighbouring countries (Colombia and Brazil) suggested the illness would be present in Venezuela as well. Physicians, policymakers and local government officials were operating with little information, limited supplies, frequent power outages, and misleading information from government authorities.

We convened with a group of clinicians, students and interns to begin efforts to identify the agent(s) of presumed arbovirus-caused illnesses in Barquisimeto. Once the inclusion criteria and hospital protocols were established, we trained volunteers to collect and store urine, plasma and saliva specimens in a liquid nitrogen tank that we had purchased from a local cattle rancher. The specimens were shipped on dry ice to the University of Florida, where they were screened for ZIKV RNA  by RT-PCR, and attempts were made to recover (“grow”) the virus in cell cultures.

Zika virus and other viruses were confirmed in patients

In early 2016, Venezuela was experiencing a long drought. We therefore expected that transmission rates of arboviruses would be low, however, because of widespread water shortages, people were storing water in containers which then became breeding grounds for mosquitos such as Aedes aegypti and Aedes albopictus, which are common vectors of chikungunya, dengue and other viruses (including Zika).

Unofficial reports based on clinical diagnoses estimate that the incidence of ZIKV infections in Venezuela in 2016 was 2,057 per 100,000 (2). In our ongoing studies, one of the patients who was infected with ZIKV was a woman who was breastfeeding her five month-old child. Both the mother and the child were positive for the virus, including the mother’s breast milk. Phylogenetic analysis of the genomic sequences of ZIKV isolated from both patients suggests that breastfeeding is a possible route of transmission, as both sequences were essentially identical (3).

The incidence of dengue virus infections in Venezuela has increased in the last decade: Venezuela has one of the highest numbers of Dengue Fever (DF)-like febrile illness cases in the American continent (4). In our study, several patients clinically diagnosed with ZF instead had DF. For example, we detected Dengue virus type 2 in a patient with haemorrhagic fever, and Dengue virus type 4 in two patients diagnosed with ZF.

Madariaga virus, a member of the South American Eastern Equine Encephalitis viruscomplex, was detected in one of the patients with suspected ZF (5). As in a previous outbreak, this case was detected in the context of an outbreak of equine encephalitis that was occurring in the region due to a shortage of vaccines against Venezuelan Equine Encephalitis Virus (VEEV). The symptoms of MADV and its close relatives range from mild febrile illness to encephalitis and death (6). Little is known about the transmission dynamics and epidemiology of Madariaga virus in humans; however it is suspected that the incidence of Madariaga virusis higher than previously thought.

Arbovirus surveillance: broadening the scope of the search

Because we utilize both molecular diagnostic techniques and virus isolation in cell cultures, we are able to broaden the scope of our search and identify other possible causes of arboviral disease in Venezuela. This combined approach is difficult and expensive to implement in most resource-strapped diagnostic laboratories; however it is a valuable tool for developing a more accurate picture of the potential cause(s) of an arbovirus epidemic. In many cases, concurrent epidemics due to more than one type of arbovirus occur during what is thought to be a single epidemic, as exemplified by cases of DF and ZF at the same location at the same time period in Barquisimeto. Moreover, in some cases, co-infections by more than 1 type of virus occur, further complicating the diagnosis without confirmation through laboratory tests.

As shown by our example, international collaborations can be helpful when in-country public health and pathogen surveillance systems are in disrepair. Our findings shed light on the complexities of arbovirus outbreaks, and confirmed the presence of ZIKV infections in Barquisimeto. The international community should always take notice; uncontrolled outbreaks in one country potentially cause a domino effect, spreading to surrounding countries.

Zika virus was discovered in Uganda in 1947 and is primarily transmitted by mosquitoes (1). Infection with the virus can cause mild symptoms, such as rash and fever. However, most infected individuals do not have any symptoms. Over the past six decades, Zika virus only caused sporadic outbreaks. Endemic circulation was confined to regions in Africa and Asia where mosquitoes of the Aedesspecies were present; the same mosquitos that are responsible for the transmission of Dengue virus and Chikungunya. Zika virus spread to Yap Island in the Pacific Ocean in 2007 and to French Polynesia in 2013. From there, the virus spread to Brazil in 2014. In a short time span, the virus covered much of the American continent that harboured the Aedes vector (2).

The introduction of the virus on the American continent allowed the virus to spread in a large immunologically naïve population with attack rates, the percentage of the population infected during the outbreak, of up to 70%. During the outbreak, and for the first time in the history of the virus, adverse outcomes that appeared to be linked with the outbreak were seen on a large scale: clusters of babies born with microcephaly,a congenital malformation resulting in smaller than normal head size for age and sex, and older children and adults with acute autoimmune neurological symptoms. The size and impact of these adverse outcomes led the World Health Organization (WHO) to declare the outbreak as a Public Health Emergency of International Concern (PHEIC) on February 1, 2016 (3).

Besides transmission through mosquitos, it appeared that Zika virus could be transmitted by sexual contact as well (4), a feature not observed in any other flavivirus before. Sexual transmission increases the geographic reach of the virus, since the virus is not bound anymore to regions that harbour the right species of mosquito. Travellers infected with Zika virus returning to regions without endemic spread of the virus can transmit the virus to their sexual partners, and potentially spread the disease further within their sexual networks.

From the onset of an infectious disease outbreak, there is a need for public health guidance. In order to inform public health guidance, one needs to understand the potential risks that are associated with the outbreak. At this stage, however, large scale studies providing robust evidence are lacking, and evidence only slowly accumulates as the outbreak expands. Here I discuss how our research group from the Sexual and Reproductive Health Group of the Institute for Social and Preventive Medicine of the University of Bern approached two challenges that the Zika virus outbreak presented, as a newly re-emerging infectious disease about which very little research about infection in humans had been done. First, establishing causality in the absence of high quality epidemiological studies. Second, establishing the risk of sexual transmission in the presence of multiple transmission routes.

Causality between Zika virus and adverse neurological outcomes

Causal inference is the process of drawing the conclusion that an outcome derives from an identified mechanism, or cause. Our aim was to determine whether Zika virus causes adverse neurological outcomes. Large scale randomized controlled trials (RCTs) are regarded as the best study design to answer causal questions. There are, however, no vaccines or treatments for Zika at present and hence no RCTs conducted. Observational studies, such as cohort studies or case-control studies, provide evidence about epidemiological associations. However, this is prone to biases or factors that might complicate the interpretation of causality. Early during the Zika virus outbreak, none of these types of studies was available, and we had to rely on evidence from case reports, case series, modelling studies and laboratory studies.

We used the approach outlined by Bradford Hill to examine the evidence for causal associations between Zika virus infection and the congenital abnormalities and Guillain-Barré syndrome (5). Bradford Hill listed nine ‘viewpoints’ from which to study associations between exposure and disease. These viewpoints are not strict rules, but can be used to decide if there is any other more likely explanation than cause and effect. We used these viewpoints as the basis for a causality framework, which enabled us to assess the full body of evidence and keep adding to it as new data emerges (6). We addressed specific questions in the domains of temporality, biological plausibility, strength of association, exclusion of alternative explanations, cessation, dose–response relationship, animal experimental evidence, analogy, specificity and consistency of findings (Box 1). A systematic review of the evidence led to the conclusion that Zika virus was the cause of microcephaly and Guillain-Barré syndrome (6). On September 7, 2016, the WHO published their causality statement based on this assessment. At present, we are keeping track of the evidence to see if our conclusions stay valid over time (7).

Risk of sexual transmission of Zika virus

Unravelling the proportion that sexual transmission contributes to the total transmission of Zika virus is complicated by coexistence of multiple transmission routes. In a region where Zika virus is endemic, it is difficult to identify sexual transmission as the cause of an infection, or whether the infection may be explained by the presence of mosquitoes. To assess the risk of sexual transmission in absence of mosquitoes, we can use data from travellers; people visiting countries that have active transmission of Zika virus who then return back to their sexual partners in countries without Zika virus. Fitting a transmission model to data from such cases in the US enabled us to estimate the risk of transmission per sex act (8). We estimated that the probability of sexual transmission of Zika virus was 1.6% (95% CI: 1.1-2.4%) per sex act. This parameter can then be used to help infer the risk of transmission or the proportion of cases due to sexual transmission in endemic regions.

Informing mathematical models with the most up to date parameters is crucial to keep modelling estimates current and relevant. To this end, we established a framework that divides transmission into its key parameters: susceptibility to infection, incubation period following sexual transmission, serial interval between the onset of symptoms in a primary and secondary case, duration of infectiousness, basic reproduction number R0, probability of transmission per sex act, and transmission rate (9). Combining the available evidence on sexual transmission of Zika virus has led to the conclusion that sexual transmission of Zika virus poses a small risk, that sexual transmission is more likely to happen from men to women than from women to men, and that sexual transmission alone will not be sufficient to sustain an outbreak. By continually updating the parameters with the most recent data, we ensure that the modelling estimates are up to date.

In conclusion, applying conceptual frameworks supports the systematic assessment of the limited evidence base during disease outbreaks. The causality framework based on Bradford Hill’s viewpoints and the sexual transmission framework allows taking into account the full spectrum of the evidence and help inform guidance. Mathematical modelling helps filling knowledge gaps by making efficient use of the available data. The generalisability of both the frameworks and the modelling makes them excellent tools to tackle similar challenges during future outbreaks of emerging infectious diseases.

Acknowledgement: My thanks go out to the team from the Sexual and Reproductive Health Group of the Institute for Social and Preventive Medicine of the University of Bern: Nicola Low, Christian L. Althaus, Kaspar Meili, P. Hung Nguyen, Maurane Riesen, Dianne Egli-Gany.

Ebola virus disease is an infectious disease that has particular significance for Africa. Historically the disease was known as Ebola haemorrhagic fever, but the change in name is reflective of the broader range of symptoms. However, no matter the name, Ebola is an evocative word. The strength of feelings of fear and perhaps fascination brought upon by this word is probably due to the very high case fatality rate of the disease, with an average of one in every two people that contract the virus dying, and because the outbreaks in different African countries have been sporadic and unpredictable (1).

The first known Ebola virus disease outbreaks were identified in 1976. One outbreak was identified in Nzara, Sudan, and the other in Yambuku, in what was then Zaire, now the Democratic Republic of the Congo (DRC). The Ebola River nearby Yambuku gave the disease and virus their names. Up until 2018 31 human index cases have been reported, sometimes with multiple separate transmission events from wildlife in one location. Fewer than two thousand cases were reported in the majority of those outbreaks, but nearly 30,000 cases and over 11,000 deaths were reported during the 2013-2016 West African epidemic (1).

The latest outbreak is ongoing in DRC at the time of writing and it is currently unknown if this was initiated through a single index case or more than one spill over event from wildlife.

The predictability of the outbreaks is reduced by the fact that the ‘reservoir hosts’ of the viruses that cause this disease are not known for certain. Fruit bats are believed to be the common hosts in nature but there is still uncertainty regarding this (2) because most outbreaks in people are not linked directly to bats, but to other mammals. In particular Africa’s great apes, gorillas and chimpanzees can be victims of the disease and sources for human infection. The Ebola virus disease outbreaks outside Africa were also linked to primates, despite studies identifying bats and pigs as possible reservoir and amplifying hosts respectively. Indirect evidence of bats in Africa as ebolavirus reservoir hosts includes the identification of a range of related filoviruses in bats, including Marburg viruses in Africa, Reston ebolavirus in Asia, and Lloviu cuevavirus in Europe. Additional uncertainty arises because most of the evidence is ecological or from serological data with little direct evidence of active infection through virus isolation.

Modelling Ebola virus dynamics

There has rightly been a focus on modelling Ebola disease in people, both during and after the 2013-2016 West African outbreak (3) and this has informed epidemic control strategies. Less attention has been given to modelling the initial ‘spillover’ events from other species to people, or disease dynamics in reservoirs, because of a lack of data. However, because the wildlife reservoirs and mechanism of spillover are poorly understood, modelling approaches can be used to identify or exclude hypotheses even when data are limited.

Modelling efforts to understand the infection dynamics in and outbreaks from wildlife to date have included a range of approaches to address different questions. Walsh and colleagues used phylogenetic models that estimate the relationship between organisms and genetic sequence data, to better understand the spread of Zaire ebolavirus (a viral species) (4). Their analyses of the virus genetic data and corresponding location data for viral isolates, placed the Yambuku viruses near to the root of the Zaire ebolavirus phylogenetic tree, suggesting that all other known outbreaks had descended from a virus closely related to this one. Although their analysis only contained a few viral fragments, it suggested that later outbreaks may have been epidemiologically linked to these and have occurred in a wave like pattern, spreading at approximately 50 km per year. Once Zaire ebolavirus RNA fragments were discovered in bats (which remains the only molecular evidence of Zaire ebolavirus infection in bats), the same team used similar models to reconstruct the ancestry of Zaire ebolavirus including fragments of viral RNA from bats (5). Their analyses suggested that all the genetic variation present in Zaire ebolaviruses, including from fruit bats, was the product of mutations accumulated within a 30 years’ time period, thus supporting the recent ancestry of Zaire ebolavirus in bat reservoirs and supporting their role in the epidemiology of Zaire ebolavirus.

After the 2013 – 2016 West African Zaire ebolavirus outbreak, another group of researchers used an alternative approach to understanding ebolavirus ecology and examined the phylogeny and the geographic distribution (phylogeography) of fruit bats themselves (6). The analyses of bat cytochrome b gene sequences for geographic structure and gene flow from Central to West Africa found geographic population structure among some species, suggesting limited movement between locations, but no genetic differentiation between Central and West African populations for bats known to make seasonal movements. The authors concluded that only three species might be able to directly disperse Zaire ebolavirus from Central to West Africa. Only one, the straw-coloured fruit bat, has a low prevalence of antibodies against ebolaviruses, but the other two, the hammer-headed and Egyptian fruit bats, have higher seroprevalences, including in West Africa (2).

The lack of data relating to ebolaviruses in African bats led Han and colleagues (7) to use a generalized, boosted regression trees, machine-learning algorithm to characterize the traits of potential filovirus-positive bat species. Boosted regression uses multiple different data prediction models to come to an optimised model through using the ensemble of model results. Specific traits of bats that have been linked to all filoviruses, such as adult and neonate body sizes, reproduction, and species’ geographic range overlap with regions of high mammalian diversity made it feasible to predict which new species might be positive for filoviruses. The greatest number of most likely species were predicted to be outside of equatorial Africa, with a majority in Southeast Asia.

Predicting Ebola outbreaks

Because of the absence of good data on ebolavirus reservoirs, forecasting when and where outbreaks will occur is difficult. Piggott and colleagues (8) used boosted regression to determine the spatial risk of human outbreaks using a range of predictors, including likely bat hosts. Schmidt and colleagues (9) used another but similar machine learning approach to boosted regression, bagging or bootstrap aggregating, to model the spatio-temporal risk of 37 human or great ape Ebola spillover events since 1982. They used spatiotemporally dynamic covariates including vegetative cover, human population size, and absolute and relative rainfall over three decades across sub-Saharan Africa to demonstrate that spillover risk is greatest during transitions between wet and dry seasons. Rulli and colleagues (10) performed an analysis of how forest fragmentation of the landscape might impact disease emergence. Fragmentation was classified through identifying pixels in satellite images and evaluating changes in forest fragmentation over time, deriving fragmentation index for forested areas. These analyses suggested that ebolavirus outbreaks occurred mostly in hotspots of forest fragmentation and this is something our group in New Zealand is working on further.

Other researchers have taken a different approach to understanding viral dynamics in bats. Buceta and Johnson (11) modelled the ebolavirus dynamics using a susceptible – infected – recovered (SIR) based compartmental model, with coupling between resources and bat populations with migration. Their models supported bat mobility and spatiotemporal climate variability as a potential mechanism for spillover dynamics through the impact of these on modelled viral infection dynamics.

Host birthing patterns and virus persistence

In addition to contributing to some of the studies above, our group has previously used an SIR modelling approach to test a different hypothesis with respect to seasonal birthing of ebolavirus hosts.In other theoretical models, we were able to show that seasonal birthing may decrease the probability of pathogen persistence within populations (12). However, data suggest that Marburg viruses may persist within colonies of seasonally breeding Egyptian fruit bats (13). We used available filovirus and bat data in a stochastic SIR compartmental model to see if filoviruses might persist within isolated bat colonies and which host–pathogen relationships allow viral persistence in the populations (14). We discovered that models that predicted highly synchronous annual breeding and shorter incubation periods did not allow filovirus persistence, but bi-annual breeding and longer incubation periods, such as reported for Egyptian fruit bats in the wild and Ebola virus in experimental studies, did allow for persistence in colony sizes often found in nature. Serological data supported the findings, with bats from species with two annual birth pulses being statistically more likely to be seropositive than those with single birthing events each year, suggesting that biannual or asynchronous birthing is necessary for filovirus persistence.

In unpublished work, led by PhD student Reed Hranac, we are trying to integrate a range of the above ideas to test the hypothesis that bat host birthing cycles can help predict the spatio-temporal occurrence of spillover events. Because of the absence of bat birthing data we have predicted bat birthing across Africa based on the limited data available. We used ensemble ecological niche models that, similarly to the boosted regression, usemultiple different data prediction models to come to an optimised model (but here with different types of models), to identify three distinct annual bat birthing patterns. We have used spatio-temporal statistical models, with lagged bat birthing data and other possible covariates, such as forest fragmentation, human population density, and mammal biodiversity, to test hypotheses regarding ebolavirus spillover in Africa. Of the three bat birthing patterns, only those associated with pteropid fruit bats were significant predictors of the occurrence of ebolavirus spillover events in both humans and other mammals. The models including these predictor variables improved the prediction of outbreaks compared to models that simply included other static covariates, such as mammal diversity. The temporal lag of birthing events with outbreak events is consistent with current hypotheses (13, 14) of infection dynamics within bat populations and differences in the mechanisms of spillover from bats to humans and other mammals.

These modelling studies are beginning to bring together the different pieces of information to better understand the emergence of ebolavirus in Africa. With a better understanding it is feasible to improve surveillance both for these viruses in the field as well as disease emergence. Further research is now needed to increase the data available to update these models, beginning the iterative cycle of model-guided fieldwork (15). Together, these should help inform control measures to prevent human disease and suffering. Some control measures, such as educating people to ensure that they do not eat apes which they find dead in the forest, are not necessarily technically challenging. However, mitigating against factors such as forest fragmentation is potentially more complex as this likely requires multiple other drivers to be understood, and will require engagement of more stakeholders to be resolved.

Rabies epitomizes all the challenges of zoonotic diseases. Although the virus circulates primarily in domestic dogs, rabies causes the most concern when it spreads from animals to people, typically via a rabid dog bite. Rabies has the highest case fatality rate of any known infectious disease and causes a horrifyingly painful death, leaving families, communities and healthcare workers traumatized. Fortunately there are extremely effective vaccines that, if administered promptly after an exposure, will prevent the fatal onset of rabies. Yet despite these lifesaving vaccines, human deaths inevitably occur, because the human vaccines are very expensive, not widely available and because not all bite victims know that they need to seek care. As long as rabies continues to circulate in domestic dog populations there is an ongoing risk of human deaths. That is what motivates the need for mass dog vaccination programs which can interrupt transmission in the reservoir and eliminate the disease at its source.

International organizations recently declared their joint commitment to eliminate human deaths from dog-mediated rabies by the year 2030 (1). Their approach is underpinned by intersectoral collaboration, focusing on improving access to post-exposure vaccines, scaling up mass dog vaccination to levels sufficient to break transmission, and engaging all stakeholders, from local communities to politicians and national governments, who, by working together can rid the world of this preventable disease. As part of the ‘Zero by thirty’ campaign, international organizations have taken major steps to catalyse progress.

Intradermal PEP regimen

In 2016 the WHO convened a Strategic Advisory Group of Experts (SAGE) working group to review the latest evidence on human rabies prevention. One challenge is that the course of post-exposure prophylaxis (PEP) to prevent rabies after an exposure is complicated. Furthermore, bite victims are often delayed in starting their PEP course because they need to raise funds to pay for the vaccines, or they need to find a health facility with the vaccines in stock. Even the costs for travel and accommodation to complete the course can be substantial, given that PEP is usually only available in major urban centres.

Various PEP regimens are recommended, some administered via the intramuscular (IM) route and some via the intradermal (ID) route. Each require different volumes of vaccines administered on different days and typically take around one month to complete, however the new abridged ID regimen is completed in one week. The clinical evidence suggests that all these regimens are extremely effective in preventing rabies (5). Experience from East Africa, and other parts of the world, indicates that delays in bite patients receiving vaccine are the main cause of PEP failures, whereby human deaths occur despite a patient receiving some sort of post-exposure vaccination. A priority is therefore to make sure that these vaccines are available immediately to rabies-exposed patients. This is where the benefits of ID vaccination become clear: in the event of an outbreak where limited vaccine is available, the same stockpile can treat over five times more patients using the new abridged ID regimen compared to IM regimens that are currently used (3).

ID regimens for rabies post-exposure vaccination have been recognized as safe and effective for over two decades (4), but have not been widely adopted. This is perhaps because of the complexity of different regimens or because ID vaccination may appear trickier than IM administration. However, TB vaccination via the ID route has been routine for decades and health workers typically say that administration is very straightforward. Another issue is the practicality of sharing vaccine vials for ID use. Unused vaccine must be discarded at the end of each day because once a vial has been opened there is a risk of contamination. Discarding expensive yet lifesaving vaccine likely feels perverse for a health worker, in contrast to IM regimens where the whole vaccine vial is used and vaccine is never discarded. However, health workers often need to refer emergency patients elsewhere because of vaccine stock outs, which are predicted to occur much less frequently under ID vaccination, even with the discarding of partially used vials.

On the basis of the SAGE recommendations, the WHO updated its position on rabies vaccines (5), and now recommends universal use of ID vaccination, highlighting the new abridged ID regimen as the simplest and least expensive option for patients and governments alike. Gavi, the Vaccine Alliance, recently shortlisted rabies as being among the diseases under consideration for its 2020-2035 vaccine investment strategy, with their final decision due towards the end of this year. As part of the WHO rabies modelling consortium we examined what a Gavi investment could mean for rabies, both in terms of improving access to post-exposure vaccines and in the context of scaled up dog vaccinations (6).

Cost-effectiveness of PEP regimens and dog vaccinations

Building on previous modelling work (2), we compared different PEP regimens to understand their relative costs and benefits, including the use of the new abridged ID regimen (3). We then examined what the impact of improved access to PEP would mean under a range of different scenarios. Our modelling work shows that a universal switch to the new abridged ID regimen would cost less than is currently spent on PEP over the Gavi 2020-2035 time period, whilst treating many more people – over 15 million more bite victims (6). We assumed that Gavi support would enable bite victims to receive PEP free at the point-of-care and that this reduces delays that bite victims often face in trying to raise money to pay for PEP. As a result we estimate almost 500,000 additional human rabies deaths could be averted, compared to the current situation. In most Gavi-eligible countries, bite victims currently pay the full cost of PEP. Without a major player like Gavi facilitating a switch to more efficient vaccination regimens, bite victims are likely to bear the brunt of this market failure – which results in preventable deaths.

In most rabies-endemic countries resources are primarily focused on preventing rabies through post-exposure vaccination of those bitten by rabid dogs. While post-exposure vaccination is critical to preventing human rabies deaths, it does not interrupt transmission in the reservoir host population, so costs continue to rise and as some people do not receive vaccination some still die of rabies. Where investments have been made in dog vaccination, human deaths have declined accordingly – yet investment and collaboration across sectors to tackle rabies at its source remains a major challenge.

We therefore considered in our model the situation whereby mass dog vaccination effort is scaled up as part of the ‘Zero by thirty’ global strategy. Under this scenario, a Gavi investment is still highly cost-effective, and the global target of zero dog-mediated human rabies deaths can be achieved. One potential concern for Gavi, and for countries tackling rabies in general, is how to prevent the escalation of costs for provision of PEP even when the incidence of rabies declines. This is because with greater awareness of the need to seek care in the event of a dog bite, and of the need to provide PEP, precautionary use of PEP rises. However, we modelled a scenario with the use of integrated bite case management (IBCM) to address this concern (7, 8). We found that IBCM dramatically increases the cost-effectiveness of PEP, whilst also acting as a sensitive tool to improve detection of rabies (9), which is critical as elimination is approached.

Like many zoonoses, rabies has until very recently been very much a neglected disease, with thousands of deaths occurring every year in low- and middle-income countries. But recent in-country prioritization exercises have highlighted that rabies is a priority for countries like Kenya. By modelling the different tools that can be applied to help us to reach the 2030 target, we hope to support governments and international agencies and demonstrate how, through collective action, human deaths from dog-mediated rabies can be eliminated. What this shows us for now is that we need to use both human and animal vaccines more effectively to deliver on this possibility.

Emerging, zoonotic, and vector-borne diseases are often lumped together in a seemingly hodge-podge “other” category of infectious diseases. For example, the mandate for South Africa’s National Centre for Emerging Zoonotic & Parasitic Diseases (CEZPD) includes pathogens as diverse as plague (a bacterial pathogen transmitted by fleas), Rift Valley Fever Virus (a mosquito-borne virus that predominantly affects cattle), and Toxoplasa gondii(a protozoan parasite transmitted by cats and other animals), to name just a few. All of these pathogens can infect and cause disease in humans, though clinical diagnosis is often difficult because the symptoms resemble those associated with many other infections.

If these pathogens are so different, why are they grouped together? I think the answer initially lay in idiosyncrasies of their epidemiology. Emerging infections characteristically cause infrequent outbreaks that are unpredictable in space and time – and most are zoonotic in origin (i.e., transmitted from animals to humans). In addition, zoonotic diseases (zoonoses) are most common in rural areas, where human contact with other animals, particularly wildlife and farm animals, is relatively frequent. Rural communities are frequently underserved, particularly in resource-poor regions, often making the recognition of these infections sporadic, whether or not this reflects an underlying pattern of sporadic incidence. Vector-borne diseases are also often zoonotic (with some major exceptions – e.g., falciparummalaria), and are typically highly seasonal, reflecting environmental drivers of vector abundance and activity. In their own ways, diseases in each of these three overlapping groups are therefore ‘occasional’ problems, such that – at least from a medical perspective – they command only part-time attention. As a result, it is efficient to allocate resources in a way that they can be shared across multiple pathogens. The resulting institutional structures developed to reflect these allocations and ultimately provided researchers, public health workers, and clinicians with experience working on a highly diverse set of pathogens. Working across these pathogens has allowed researchers to generalize and begin to identify broader patterns that point towards common underlying drivers of, as well as differences between, emerging, zoonotic, and vector-borne infections.

Another factor that these pathogens have in common, aside from their intermittent detection, is that only limited headway can be made in understanding and addressing them through medical science alone. It has long been recognized that addressing zoonotic and vector-borne diseases requires veterinary and entomological perspectives, which has forced collaboration across disciplines in a non-traditional way relative to other areas of medicine and public health. This history has perhaps made the area particularly receptive to influences of and interactions with other disciplines, including ecology and the social sciences.

Finally, emerging diseases require rapid intersectoral cooperation for effective intervention. The ongoing epidemic of Ebola in the Democratic Republic of Congo highlights the advances that have been made in this arena since the 2014-2016 Ebola epidemic in West Africa. Whereas the latter eventually saw involvement from government, business, academia, and the civil sector (including philanthropic and nonprofit organizations), all of these actors were engaged within the first 10 days of the response to the current epidemic [1].

The combination of the generalization that emerges from working across pathogens, the necessity of interdisciplinary perspectives, and the need for a multisectoral response, all under the umbrella of ‘emerging, zoonotic, and vector-borne infections,’ has led this area of epidemiology to become a testing ground for pushing boundaries in public health. Recently, a further step has been taken – this time, attempting to push temporal boundaries by preparing to combat highly lethal zoonotic infections with the capability for human-to-human transmission – such as Nipah virus, Middle Eastern Respiratory Syndrome Coronavirus, and Lassa virus – before they cause self-sustained epidemics. The central player in this endeavour is the Coalition for Epidemic Preparedness Innovations (CEPI), which is bringing together expertise and resources from across sectors to develop pipelines for vaccine discovery, development, and eventual deployment. While it may be many years before we know whether the investment has paid off, this bold initiative shows that the history of collaboration and broad perspectives developed through the study of emerging, zoonotic, and vector-borne diseases still has a lot to offer in terms of innovative approaches to public health.

In this issue of the Quarterly, you will find articles from authors who have crossed many types of boundaries in their work on emerging, zoonotic, and vector-borne diseases. Gabriela Blohm, of the University of Florida, describes how her cross-cultural childhood experiences have shaped her scientific goals and her passion for improving arbovirus surveillance in Venezuela. David Hayman investigates various hypotheses regarding how Ebola virus is maintained in wild animals and potential mechanisms of how the virus has spread through the African continent. Michel Counotte explores conceptual and quantitative frameworks for understanding Zika virus epidemiology in endemic and epidemic settings. Samuel Alizon describes methods in phylodynamics that bring together epidemiological and evolutionary perspectives to infer epidemiological parameters from genetic sequence data. Finally, Thumbi Mwangi and Katie Hampson discuss their work towards the global elimination of canine-mediated rabies, which requires both international and intersectoral cooperation on a broad scale. Together, the authors represent a diverse array of scientific perspectives from around the world, bringing a wide range of epidemiological approaches to bear on emerging, zoonotic, and vector-borne diseases.

The human immune deficiency virus (HIV) and human papillomavirus (HPV) are two heavy hitting sexually transmitted infections (STIs). HIV has crippled the social structures and economies of countries in Sub-Saharan Africa and has led to an unprecedented response in research and fund raising. The prevalence of HIV worldwide has mostly stabilised with the widespread availability of antiretrovirals, but the number of new infections that occur yearly is still unacceptably high. HPV is the most common STI globally, the necessary cause of cervical cancer and also leads to genitals warts and other male and female genital cancers. As expected, because of the common mode of transmission, co-infection rates are high. It has also been easy to show empirically that HIV co-infected individuals are more likely to have persistent HPV infections and are more likely to progress to HPV related disease.

Associations between prevalence of the one infection and incidence of the other have also been estimated empirically. Meta-analyses of the association between HPV prevalence and HIV acquisition and the association between HIV prevalence and new HPV detection have estimated a two-fold increased risk in both directions, after adjusting for individual-level behavioural factors such as marital status and the number of recent sexual partners. The studies argue that biological mechanisms may be responsible for these increased risks and hence primary prevention of the one infection may reduce incidence of the other, but they also concur that residual confounding due to behaviour at the sexual network level cannot be ruled out. We used an individual based model to shed some light on the matter.

We adapted an existing HIV-STI model, MicroCOSM (1), to include infection with 13 oncogenic HPV types (2). The model population represented the South African population by age and sex and there was individual level variation in sexual behaviour. The model was fitted to HIV and type-specific HPV prevalence data using a Bayesian approach. The model world represented the null hypothesis that infection with HIV does not increase susceptibility to or infectiousness of HPV, and vice versa.

Using 500 parameter combinations from the posterior distributions of the parameters for each HPV type, we simulated 500 cohorts similar in design to the studies that estimated transmission associations between HIV and HPV: individuals were tested for HIV and HPV every three months for three years. We used these simulated cohorts to perform statistical analyses similar to those conducted in the empirical studies. For example, the Cox proportional hazards model was used to calculate hazard ratios (HRs) to assess association. A HR of 1 means that there is no association between the ‘exposure’ and the ‘outcome’. A HR of greater than one means that the ‘exposure’ increases the risk of the ‘outcome’. Since these two STIs have the same mode of transmission, we expected the HR to be greater than one. We then controlled for the sexual behaviour indicators that most of the empirical studies adjusted for – age, marital status and number of new sexual partners in the preceding 6 months. As stated earlier, there were no direct biological effects on transmission of one infection in presence of the other in our model world. Hence, we expected the HRs after controlling for sexual behaviour to become closer to one.

The mean of the unadjusted HRs from the 500 cohorts for the association between HPV prevalence and HIV acquisition was 2.6 (95% CI 2.2-3.1). After adjusting, the HR remained significantly greater than one: HR=1.8 (95% CI 1.3-2.2). The mean unadjusted HR for the association between HIV prevalence and new HPV detection was 2.5 (95% CI 2.2-2.8) and also remained significantly greater than one after adjustment: HR=2.0 (95% CI 1.8-2.3). These adjusted estimates are very similar to the adjusted estimate of association found in meta-analyses and led us to the conclusion that direct biological effects on transmission are not necessary to reproduce the empirical estimates.

In our simulated data, we can calculate measures of network level effects. For example, we can calculate the size of each individual’s sexual network by counting all individuals linked to each other at one point in time. This measure is extremely difficult to accurately obtain in observational studies. Also adjusting for this measure brought the associations much closer one, thus confirming the importance of network-level effects. These findings were consistent in multiple sensitivity analyses. We also included direct biological effects in our model world, and although simulated measures of association were greater than in the model world without these effects, they still compared well to empirical estimates.

To get back to our question: are associations between HIV and HPV transmission due to behavioural confounding or biological effects? We cannot rule out the possibility of biological mechanisms of increased transmission of one infection in presence of the other, but observed associations can be explained entirely by network-level effects that observational studies cannot account for.

The far-reaching, highly ambitious Sustainable Development Goals (SDGs) build upon the momentum generated by the Millennium Development Goals (MDGs) and are intended as a guide for health, social and economic initiatives until 2030 (1). As with the MDGs, the SDGs are likely to influence the allocation of resources for global health programmes. Issues that are not included in the SDGs may receive less attention and funding, even if the issue is of significant importance. During the time of the MDGs (2000-2015), for example, spending by some donor agencies on non-communicable diseases like diabetes was actually higher in the 1990s than in the late 2000s, possibly as these diseases were not included in the MDGs.

There are seventeen SDGs, with SDG 3 being specific to health. The 3rd SDG aims to ensure healthy lives and promote wellbeing for all, throughout the lifespan. The goals address a wide range of conditions, more so than with the MGDs. SDG-3 also goes beyond a biomedical approach to disease and expressly acknowledges that health cannot be attained without social and economic changes.

Where do STIs fit within the SDGs?

At first glance, however, the place given to health appears somewhat diminished in the SDGs, where health constitutes only one of seventeen goals, while in the MDGs three of the eight goals concerned health. This observation might be true for health in general, but the SDGs give particular emphasis to conditions related to sexual and reproductive health (2). There is indeed much cause for optimism for services such as for family planning and for treating sexually transmitted infections (STIs). Sexual and reproductive health and rights are included as specific targets under both the health (SDG-3) and gender (SDG-5) goals. Notably, achieving gender equity is a standalone goal in the SDGs, something that gender advocates fought hard to achieve. Progress with empowering women would lower their vulnerability to STIs, violence, and the health consequences of fewer economic and social opportunities, all of which are inter-linked. While the focus on sexual and reproductive health is encouraging, there is also cause for pessimism in the STI field. There is no direct mention of the term ‘STIs’ within the SDGs, while several other communicable diseases are specifically named. Also missing is a direct reference to adolescents’ rights to sexual and reproductive health interventions, including comprehensive sexuality education. This is disappointing as there had been much advocacy for the specific inclusion of adolescents in the long lead-up to the SDG declaration.

Two other distinctive features of the SDGs bear mention. Firstly, the goals were designed to be cross-cutting, forming a ‘network of targets’ (3), wherein each target explicitly refers to multiple goals (4). Though this approach may appear unnecessarily complicated, the aim is to build a coherent approach between health services, and, for example, education and other initiatives to reduce inequalities, trying to avoid silo-like activities. The connections between different areas are especially important for the control of STIs. STIs would be reduced by advances in the quality of healthcare and education in general (SDG-3 and 4); greater gender equality (SDG-5); reductions in inequality and stigma (SDG-10); better economic growth and decent work (SDG-8); safer cities (SDG-11); and stronger partnerships for research and sustainable development (SDG-17).

A second defining feature of the SDGs is that the goals apply to all countries, regardless of income levels. The broad initiatives that are envisioned within the SDGs have global relevance, especially those that counter inequalities. This aims to challenge the modus operandi of policy makers and researchers alike, across the world. This is important as, unlike many other diseases, STIs are a significant contributor to the disease burden in all countries. Potentially, then, it is possible to develop one cohesive global STI control strategy that can be applied universally to all countries, regardless of economic status.

Framework for advancing STI control within the SDGs

We propose a framework for refocusing attention on the control of STIs in the forthcoming years, most especially within low- and middle-income countries (LMICs). The text mainly pertains to STIs other than HIV, as HIV considerations often differ from those for other STIs.

STI services hold many competitive advantages in the SDG era. Fundamental needs should be highlighted. Importantly, the STI field needs to highlight the fact that the burden of STI disease and drug resistance is rising alarmingly in many settings. There are significant gaps in service delivery for STIs. Moreover, services for controlling STIs have been given little attention by the large global funders, such as the Bill and Melinda Gates Foundation, and the Department for International Development is a United Kingdom. Even large commissions on health investments largely discount the value of STI control, aside from the vaccine against Human Papilloma Virus, which prevents cervical cancer and genital warts. Given this context, we propose:

  1. strategically promote a few effective and emerging STI interventions;
  2. highlight the intersections between HIV and STIs; and
  3. select a few population groups and settings to prioritise.

Strategically promote selected STI interventions

These efforts can build on momentum stemming from the success of programmes to eliminate syphilis infections in new-borns, and of the marked advances in the technologies used to diagnose STIs. A clearly defined program of work could galvanise these actions and expand the place of STIs within the global policy agenda.

Some STI interventions appear well suited to the SDG era. In particular, the use of tests done at the time of a patient visit (point-of-care tests). The Human Papilloma Virus vaccine is already considered an intervention of high global importance and could spearhead STI control progress. A vaccine against Herpes Simplex Virus would also spur the field on; The World Health Organisation considers that vaccine among the top 10 priority vaccines to be developed (5).

There is good evidence on most of the steps needed to ‘end/eliminate STIs public health impact by 2030’, and doubtless, new exciting interventions will emerge. Together these must capture global position, imagination and funding spaces. Lastly, as with all infectious diseases, the STI field needs to demonstrate it can respond effectively to outbreaks of these infections, including outbreaks involving drug-resistant microbes.

The opportunity for a fresh start gives the STI field a chance to move on from any previous failures in research or programming, and to renew its focus on things that will work well. Noting programme and research successes and being clear on how to propagate them will provide areas to be championed, for which, the SDG era is crying out. This era is seeking compelling approaches where success can be demonstrated – the highlighting of solutions, rather than the demonstration of need or gaps in services. Several notable examples of success already exist. For instance, with a comprehensive program, syphilis declined in many population groups in China (6). Also, in Cuba elimination of syphilis in new-borns was achieved (7). Appreciable declines in the incidence of genital ulcers and increasing access to Human Papilloma Virus vaccination are all clearly causes that can be championed.

Further mend the ‘fractured paradigm’ between HIV and STI

In recent years, the control of syphilis has been enhanced by integrating syphilis and HIV programmes. The joined-up nature of these efforts neatly reflects the core principles of the SDGs. The SDG era provides the perfect foil for mending the ‘fractured paradigm’ (8), between HIV and other STIs. This paradigm has been as counterproductive for HIV as it has been for non-HIV STIs. In many countries, during the MDG period, basic STI services were left in disarray as STI program resources dwindled. The deterioration in these services raised STIs, which are a significant driver of HIV transmission. Any further weakening of STI control may well undermine progress made in HIV prevention. Fundamentally, more extensive STI control is feasible, and HIV prevention can be strengthened in doing so.

Many examples illustrate the potential synergies between HIV and the STI field, which are essentially inseparable areas. Examples include sex condom provision, reductions in gender-based violence and optimised services for sex workers Well-developed HIV services, such as clinics for antiretroviral therapy, provide useful platforms for collaboration. Further initiatives aiming for convergence between HIV and other STIs could form central pillars of STI approaches to the SDGs.

Focus on vulnerable groups and on equity gains

The predilection of STIs for women and for vulnerable populations makes these infections intrinsically inequitable. Services that ameliorate STIs, by their nature, thus enhance equity. Framing STI services as a key vehicle for reducing health and other inequities is potentially of much strategic value.

Some population groups are central to both the STI field and the attainment of the SDGs. Young women (15-24 years), in particular, are arguably the highest priority group for STI control and are given centre-place within the SDGs. The growing attention and funding for this group could be channelled into combatting the complex multi-sectoral factors underpinning their heightened vulnerability, including to STIs. STI services in Africa and for migrant women also warrant attention, especially the targeting of young women. Presenting STI interventions as an important means of attaining youth and migrant goals, for example, might well gain some traction.

Addressing vulnerability includes lowering the financial barriers to service access. Many intersections between health financing and STIs remain unexploited, especially financial incentives for people to access services. Giving people money, for example, for bringing their sexual partner to the clinic for treatment ticks many of the SDG boxes. Money could also be given to sex workers or men who have sex with men for attending STI services for testing and treatment. Also, links could be made with the private sector who provide much of the treatment for STIs globally. Public-private sector initiatives are possible, again consistent with the SDG framework.

Way forward

The SDGs present an opportunity to reimagine and then reconfigure global health, and to make health central to sustainable development. The global health community, however, is yet to take on board the implications of ‘sustainable development’ fully. Failure to do so risks relegating the SGDs to the pile of previous failed health initiatives (9).  

In particular, the STI field as a whole needs to develop a response to the question: ‘Given the nature of the SDGs, how do we go about justifying investment and accelerating progress in STIs in this new climate?’. Business as usual is unlikely to work, it had mixed success in the MDG era, and might even do worse under the SDGs. There is a considerable risk of getting lost in the ocean of competing priorities in this time of the SDGs. STI global leaders, researchers and services themselves will need to be carefully aligned with the case made. A large commission involving potential funding agencies, STI experts and policy leads could be set up to examine the opportunities and priorities for STIs in the next fifteen years, and to present a focused program of work. Commissions, STI conferences and a series of catchphrases could shape the vision and strategies around STI in this era.

Implemented correctly, the STI agenda may well fit better within the SDGs than the MDGs. Each disease area needs to pro-actively make their case in these early years of the SDGs, noting how they contribute to other disease areas and several SDG targets. Paradoxically, it might be best to strongly promote only some STI interventions, ones which are integrative, have multiple impacts and can champion STIs role in attaining the SDGs. The alternative, presenting arguments for comprehensive packages of clinical services, risks getting lost in the relative complexity of the SDGs.

Sustainable development prerogatives have already fomented global shifts (in understanding of climate change, for example). Can the SDGs also usher in a golden era for STIs? Quite possibly, an end to STIs as a public health problem is possible by 2030, with a pro-active, focused agenda crafted around a few compelling interventions relevant to all countries, synergised with HIV and targeted at vulnerable populations.

One hundred years ago the First World War ground to an end. After five years of slaughter and the deaths of an estimated seventeen million people, the Armistice was to be signed at the 11th hour on the 11th day of the 11th month of 1918. South Africans of all races fought with the Allies, and more than ten thousand lost their lives (1). In those days young English women were told: most of you will never marry because all the men are dead (1); however, none imagined that another disaster was about to strike (2-4).

Among the three greatest pandemics in history are the Black Death (5), the Spanish Flu (3, 6, 7) and now HIV (8). The Black Death was bubonic plague caused by the bacterium Yersinia pestis which killed an estimated 50 million people or about half the population in Europe, over several decades in the 14th century (5). The Spanish Flu which was first reported in Spain (9), but did not start there, was caused by a virulent strain of the H5N1 virus and killed up to fifty million people, or 2% of the world’s population, most of them in less than one month in 1918 (10). Now we are dealing with HIV which has killed an estimated thirty-five million people over thirty years and the pandemic continues (11).

The Spanish Flu struck in three short waves (10). The first wave resembled typical flu epidemics in which the sick and elderly were at the greatest risk, while younger, healthier people recovered. In civilian life, those that are very sick stay home while those that are mildly ill continue with their lives and spread the mild strain. When the second wave struck the virus had mutated to a deadlier form and soldiers with a mild strain stayed where they were while the severely ill were sent on crowded trains to crowded field hospitals, spreading the deadlier virus. The most vulnerable people were, like the soldiers in the trenches, young, otherwise healthy adults (12). The third wave was again a more typical and comparatively mild epidemic.

Perhaps the most remarkable aspects of the epidemic were the speed at which it spread and the rapidity with which it killed but the reasons for this are still debated. In India where seventeen million people may have died (13), mortality began in Mumbai (Bombay) early in October 1918. By the middle of October people were dying in the West and the South; by the middle of November mortality in the West and South of India had fallen and the epidemic had spread to the North and East. By the middle of December, it was almost entirely limited to the North-East, and by the end of December, it was over. The median time to death was ten days (14) and some died within hours of showing symptoms.

Symptoms in 1918 were so unusual that influenza was initially misdiagnosed as dengue, cholera, or typhoid. Among the most striking complications were haemorrhage from mucous membranes, especially from the nose, stomach, and intestine, bleeding from the ears and haemorrhages in the skin. The enormous death toll was caused by the high infection rate of up to 50% and the high case-fatality rate of 2.5% as compared to less than 0.1% in most flu epidemics. The majority of deaths were from bacterial pneumonia, a secondary infection caused by influenza, but the virus also killed directly, causing massive haemorrhages and oedema in the lung (4). The severity of the symptoms suggests that it may have been caused by cytokine storms as the immune system fought to overcome the infection (12).

South Africa was not exempt from the Spanish Flu; and the epidemic there was extensively recorded, reported and analysed in the seminal work of Howard Phillips in his book and thesis Black October (15, 16). Phillips discussed in detail the course and impact of the epidemic on The Rand, Cape Town, Kimberly, Bloemfontein and the Transkei as well as the nature and attempted treatment of patients, popular and religious explanations of why it happened and the way in which it changed public health. One cannot begin to do justice to his extensive work and analysis, but some particular points and observations are worth noting (15, 16). The infections that started the second, deadly wave, arrived with two troop ships, the Jaroslav and the Veronej, which docked in Cape Town in September 1918. The epidemic then rose and fell with extraordinary speed peaking in mid-October falling rapidly and was over by the middle of November by which time up to half-a-million people had died. The worst affected area followed the main railway line from Cape Town to the Western Transvaal while the Ciskei and the Transkei were also severely affected. The death rate was highest in the Cape, where 3.3% of the population died, and lowest in Natal where 1.1% of the population died. About 0.8% of white people died but the mortality rate was three times higher among other race groups, and about 2.6% of black, Indian and coloured people died. Almost twice as many men as women died and about three-quarters of those that died were aged 15 to 45 years.

Epidemics have been with us for all of recorded history (17), and there will inevitably be more to come (18). We should, therefore, study the history of past epidemics and learn how to avoid, manage and control them. South Africa is still struggling to contain the epidemic of HIV and manage the epidemic of TB, now being primarily driven by HIV. Public health is everyone’s health and South Africa needs to work hard to develop a robust and universal health system that will provide the foundation for social and economic development.