Estimation of Lassa fever incidence rates in West Africa: Development of a modeling framework to inform vaccine trial design

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Abstract

Lassa fever (LF) is an acute viral hemorrhagic disease endemic to West Africa that has been declared a priority disease by the World Health Organization due to its severity and the lack of a vaccine or effective treatment options. Several candidate vaccines are currently in development and are expected to be ready for phase III field efficacy trials soon. However, most LF cases and deaths are believed to go unreported, and as a result we lack a clear understanding of several aspects of LF epidemiology and immunology that are critical to the design of vaccine efficacy trials.

Methods

To help guide vaccine trial design and trial site selection we estimated the force of infection (FOI) from rodent hosts to humans in all 1 st and 2 nd administrative units in West Africa from published seroprevalence studies. We next estimated LF reporting probabilities using these FOI estimates and LF case and death reports and then projected FOI in all admin1 and admin2 areas without seroprevalence data. We then extrapolated age-specific LF incidence rates from FOI estimates under different assumptions regarding the level of protection against reinfection among seropositive and seronegative individuals with a history of prior infection.

Results

Projected FOI estimates and modeled annual LF incidence rates indicate that Sierra Leone, southern Guinea, and a few areas within Nigeria would likely experience the highest LF case incidence rates for a vaccine trial. Estimated LF incidence rates were highly sensitive to assumptions about Lassa immunology, particularly the frequency of seroreversion among previously infected individuals and the extent to which seroreverted individuals retain protection against reinfection and more severe disease outcomes.

Conclusions

Our spatial LF incidence rate estimates, along with the interannual and seasonal variability in these estimates and estimates of baseline seroprevalence, could be used for vaccine trial site selection, choosing the target population (e.g., age and serostatus), and maximizing a trial’s statistical power.

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