Abstract

Human and animal trypanosomiasis, spread by tsetse flies (Glossina spp), is a major public health concern in much of sub-Saharan Africa. The basic reproduction number of vector-borne diseases, such as trypanosomiasis, is a function of vector mortality rate. Robust methods for estimating tsetse mortality are thus of interest for understanding population and disease dynamics and for optimal control. Existing methods for estimating mortality in adult tsetse, from ovarian dissection data, often use invalid assumptions of the existence of a stable age distribution, and age-invariant mortality and capture probability. We develop a dynamic model to estimate tsetse mortality from ovarian dissection data in populations where the age distribution is not necessarily stable. The models correspond to several hypotheses about how temperature affects mortality: no temperature dependence (model 1), identical temperature dependence for mature adults and immature stages, i.e., pupae and newly emerged adults (model 2), and differential temperature dependence for mature adults and immature stages (model 3). We fit our models to ovarian dissection data for G. pallidipes collected at Rekomitjie Research Station in the Zambezi Valley in Zimbabwe. We compare model fits to determine the most probable model, given the data, by calculating the Akaike Information Criterion (AIC) for each model. The model that allows for a differential dependence of temperature on mortality for immature stages and mature adults (model 3) performs significantly better than models 1 and 2. All models produce mortality estimates, for mature adults, of approximately 3% per day for mean daily temperatures below 25°C, consistent with those of mark-recapture studies performed in other settings. For temperatures greater than 25°C, mortality among immature classes of tsetse increases substantially, whereas mortality remains roughly constant for mature adults. As a sensitivity analysis, model 3 was simultaneously fit to both the ovarian dissection and trap data; while this fit also produces comparable mortality at temperatures below 25°C, it is not possible to obtain good fits to both data sources simultaneously, highlighting the uncertain correspondence between trap catches and population levels and/or the need for further improvements to our model. The modelling approach employed here could be applied to any substantial time series of age distribution data.

Highlights

  • Human and animal trypanosomiasis, which is spread by tsetse flies (Glossina spp), is a major health concern in much of sub-Saharan Africa [1,2,3]

  • Trypanosomiasis, spread by tsetse flies (Glossina spp.), is a disease that is fatal for both humans and livestock if left untreated, and is a serious threat to public health in many regions of sub-Saharan Africa

  • In order to understand the dynamics of the disease it is important to understand tsetse population dynamics

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Summary

Introduction

Human and animal trypanosomiasis, which is spread by tsetse flies (Glossina spp), is a major health concern in much of sub-Saharan Africa [1,2,3]. Studies at the station have provided improved understanding of vector and disease dynamics, with the aim of improving disease control [5,6,7]. Accurate estimates of adult tsetse mortality constitute an essential element of that understanding [10]. Laboratory animals and wild populations can differ greatly in their life expectancies [11]. To understand population dynamics in the wild, it is essential to obtain data from freeranging field populations rather than laboratory animals [11]. Mark-recapture can provide good estimates of tsetse population parameters in closed situations, where it is feasible to recapture the same flies many times during their lifetimes [12,13]. In open populations subject to in- and out- migration, the results are often difficult to interpret, and researchers have developed alternate methods for estimating mortality [10,14]

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