Estimating Leptospirosis Incidence Using Hospital-Based Surveillance and a Population-Based Health Care Utilization Survey in Tanzania

Citation: 
Holly M. Biggs, Julian T. Hertz, O. Michael Munishi, Renee L. Galloway, Florian Marks, Wilbrod Saganda, Venance P. Maro, John A. Crump
Publication year: 
2013

Background: The incidence of leptospirosis, a neglected zoonotic disease, is uncertain in Tanzania and much of sub-Saharan Africa, resulting in scarce data on which to prioritize resources for public health interventions and disease control. In this study, we estimate the incidence of leptospirosis in two districts in the Kilimanjaro Region of Tanzania.

Methodology/Principal Findings: We conducted a population-based household health care utilization survey in two districts in the Kilimanjaro Region of Tanzania and identified leptospirosis cases at two hospital-based fever sentinel surveillance sites in the Kilimanjaro Region. We used multipliers derived from the health care utilization survey and case numbers from hospital-based surveillance to calculate the incidence of leptospirosis. A total of 810 households were enrolled in the health care utilization survey and multipliers were derived based on responses to questions about health care seeking in the event of febrile illness. Of patients enrolled in fever surveillance over a 1 year period and residing in the 2 districts, 42 (7.14%) of 588 met the case definition for confirmed or probable leptospirosis. After applying multipliers to account for hospital selection, test sensitivity, and study enrollment, we estimated the overall incidence of leptospirosis ranges from 75–102 cases per 100,000 persons annually.

Conclusions/Significance: We calculated a high incidence of leptospirosis in two districts in the Kilimanjaro Region of Tanzania, where leptospirosis incidence was previously unknown. Multiplier methods, such as used in this study, may be a feasible method of improving availability of incidence estimates for neglected diseases, such as leptospirosis, in resource constrained settings.