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DISEASE ECOLOGY

Vaccination under uncertainty

A synthesis of epidemiological, laboratory and economic data provides suggestions for optimal vaccination strategies against foot-and-mouth disease in east African livestock.

Vaccination is potentially an extremely powerful tool for controlling infectious disease. However, decisions on whether and how to deploy vaccines are often complex and interdisciplinary, requiring input from fields ranging from pathogen biology and epidemiology through to economics. Optimizing vaccination deployment is especially difficult in the face of major uncertainty in any of these areas — and particularly where economic constraints limit what interventions can be afforded. A signal example of this problem is the case of foot-and-mouth disease (FMD) virus outbreaks among livestock in eastern Africa. A lack of data on the economic impact of the disease, and the existence of multiple viral strains that infect wildlife and domestic hosts, together with cost constraints precluding mass vaccination, have combined to limit design and deployment of control options. As they report in Nature Ecology & Evolution, Casey-Bryars et al.1 used a combination of socioeconomic analysis, outbreak surveillance, viral sequencing and serological surveys to provide a broad picture of this disease in the region, and recommendations for its control.

The authors first assessed the economic impacts of FMD virus on various farming systems in eastern Africa. Their extensive cross-sectional, longitudinal and outbreak questionnaires, involving numerous stakeholders, illuminate how the disease contributes to overall poverty in the region. This microeconomic analysis suggests that FMD outbreaks decreased cow milk production by 67% and goat milk production by 65%. About 70% of households reported that outbreaks also negatively affected traction capacity and crop production, and cash generation from livestock sales decreased by an average of 27%.

Next, the authors posited that the inability to deploy mass FMD vaccination in the region points towards developing a scheme of reactive targeted vaccination, based on knowledge of the spatiotemporal dynamics of FMD serotypes. Direct observation of outbreaks and parallel viral sequencing can reveal useful information on pathogen dynamics and evolution; however, outbreak samples in this setting can be sparse, especially given the relatively short, acute duration of FMD infection. The authors solved this problem with a neat integration of outbreak and viral sampling with serological analysis to detect immunity to past or recent infection (Fig. 1). Serological analysis provides integrated information on an individual animal’s past incidence of infection and exposure to different strains of FMD virus2. The authors conducted serological surveys (using pan-serotypic non-structural protein antibodies) across different livestock management systems in nine districts in three regions of northern Tanzania, with additional data being supplied by historical records from Kenya, Uganda and Tanzania.

Fig. 1: Sampling opportunities and epidemic dynamics.
figure1

a, Schematic illustration of the time course of an acute (short-duration) immunizing viral infection passing through a population, such as occurs in FMD outbreaks among livestock. b, The epidemic is captured by a simple SIR model of disease dynamics; proportions of susceptible (orange), infected (red) and recovered, seropositive individuals (blue) are presented relative to the initial number of exposed susceptible individuals. During the epidemic, timely surveillance of incidence and viral genetics can give rich information on epidemic dynamics and evolution. However, this opportunity is brief, as the epidemic rapidly extinguishes itself by depleting its susceptible ‘fuel’. By contrast, the epidemiological signal from serological studies of recovered, seropositive individuals is much more persistent, declining on the much slower timescale of population turnover.

The resulting data provide insights into key questions concerning FMD outbreaks in eastern Africa. First, the authors looked for a systematic pattern of circulating serotypes, which could be used to inform a more efficient vaccination strategy. The results suggest that there were partially predictable sequential waves of serotype outbreaks in Tanzania, and this pattern was observed broadly across eastern Africa: a wave of serotype SAT1 occurred from 2010 to early 2011; serotype O was prevalent from mid- to late 2011; serotype SAT2 from late 2011 to mid-2012; serotype A from mid-2012 to mid-2013; and SAT1 returned in late 2013. The median time between outbreaks was estimated using survival analyses to be 489 days.

Next, the authors assessed the role of wildlife (primarily the buffalo population) in driving FMD outbreaks in domestic livestock systems. Wildlife are known to play a significant role in FMD transmission in southern Africa. By contrast, Casey-Bryars and colleagues’ viral phylogenetic analysis of isolates sampled from cattle and wild buffalo in eastern Africa found no close genetic relation between cattle and buffalo isolates. This suggests that control efforts can thus be focused on livestock vaccination in eastern Africa, contrary to the wildlife-exclusion control strategies used in southern Africa.

From these combined analyses, Casey-Bryars et al. conclude that targeted serotype-specific livestock vaccination ahead of oncoming waves of infection could be an efficient control strategy for FMD in eastern Africa. They underline this potential with a vaccine-matching study based on circulating serotypes. Their findings also suggest fruitful areas for future development. First, exploring prediction of the spatiotemporal sequence of FMD virus serotypes would be a further boon to vaccine targeting, albeit a difficult problem in this epidemiological context. Such phylodynamic predictions are increasingly important in a number of contexts (for example, see ref. 3 for this concept applied to influenza), especially given the ongoing development of immune-surveillance methods2. Second, epidemiological models of FMD spread have been deployed successfully to interpret control in a number of contexts4,5 and would be a useful extension to explore the impact of uncertainties on candidate vaccination policies for FMD. For example, formulating a fully- or semi-mechanistic epidemiological model to identify important covariates of the waves and for performing forward predictions could yield valuable insights on the impact of uncertainty on what we can know about the dynamics of this system. Finally, continuing economic analyses of the cost-effectiveness of deploying prophylactic mass vaccination for eastern African FMD would seem apposite, given the impact of the disease.

More broadly, Casey-Bryars and colleagues’ work points the way for future cross-disciplinary data collection to optimize epidemic control in the face of epidemiological uncertainty and economic constraint. The tight integration of laboratory, epidemiological and social-economic methods they deployed is particularly relevant, given the key focus of the Sustainable Development Goals on poverty reduction.

References

  1. 1.

    Casey-Bryars, M. et al. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-018-0636-x (2018).

  2. 2.

    Metcalf, C. J. E. et al. Lancet 388, 728–730 (2016).

    Article  Google Scholar 

  3. 3.

    Łuksza, M. & Lässig, M. Nature 507, 57–61 (2014).

    Article  Google Scholar 

  4. 4.

    Buhnerkempe, M. G. et al. PLoS ONE 9, e91724 (2014).

    Article  Google Scholar 

  5. 5.

    Ringa, N. & Bauch, C. T. Epidemics 9, 18–30 (2014).

    CAS  Article  Google Scholar 

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Correspondence to Max S. Y. Lau.

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Lau, M.S.Y., Grenfell, B.T. Vaccination under uncertainty. Nat Ecol Evol 2, 1350–1351 (2018). https://doi.org/10.1038/s41559-018-0652-x

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