Abstract
Many infectious diseases lack robust estimates of incidence from endemic areas, and extrapolating incidence when there are few locations with data remains a major challenge in burden of disease estimation. We sought to combine sentinel surveillance with community behavioural surveillance to estimate leptospirosis incidence. We administered a questionnaire gathering responses on established locally relevant leptospirosis risk factors and recent fever to livestock‐owning community members across six districts in northern Tanzania and applied a logistic regression model predicting leptospirosis risk on the basis of behavioural factors that had been previously developed among patients with fever in Moshi Municipal and Moshi Rural Districts. We aggregated probability of leptospirosis by district and estimated incidence in each district by standardizing probabilities to those previously estimated for Moshi Districts. We recruited 286 community participants: Hai District (n = 11), Longido District (59), Monduli District (56), Moshi Municipal District (103), Moshi Rural District (44) and Rombo District (13). The mean predicted probability of leptospirosis by district was Hai 0.029 (0.005, 0.095), Longido 0.071 (0.009, 0.235), Monduli 0.055 (0.009, 0.206), Moshi Rural 0.014 (0.002, 0.049), Moshi Municipal 0.015 (0.004, 0.048) and Rombo 0.031 (0.006, 0.121). We estimated the annual incidence (upper and lower bounds of estimate) per 100,000 people of human leptospirosis among livestock owners by district as Hai 35 (6, 114), Longido 85 (11, 282), Monduli 66 (11, 247), Moshi Rural 17 (2, 59), Moshi Municipal 18 (5, 58) and Rombo 47 (7, 145). Use of community behavioural surveillance may be a useful tool for extrapolating disease incidence beyond sentinel surveillance sites.
Highlights
Our understanding of the burden of many infectious diseases in lowresource areas is hampered by few robust estimates of incidence
This study has applied and explored the limitations of a relatively simple method to estimate the incidence of leptospirosis across a broad area of northern Tanzania, including areas not served by leptospirosis surveillance
We suggest that our numerical estimates should be viewed with caution as the risk factors for leptospirosis were modestly predictive
Summary
Our understanding of the burden of many infectious diseases in lowresource areas is hampered by few robust estimates of incidence. The most rigorous approach to estimating incidence is through population-based cohort studies. Population-based approaches require substantial resources in order to recruit participants and maintain participation through the duration of the study (Szklo, 1998). Such studies have not been conducted for many infectious diseases in low-resource areas, including leptospirosis. Exposure to cattle and rodents has recently been identified as risk factors for human leptospirosis among patients with fever in northern Tanzania (Maze et al, 2018). | 498 data with data from community risk factor questionnaires to estimate the incidence of leptospirosis across a broad geographic area of northern Tanzania
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
