A Multi-Host Agent-Based Model for a Zoonotic, Vector-Borne Disease. A Case Study on Trypanosomiasis in Eastern Province, Zambia

Dispersal in heterogeneous environments drives population dynamics and control of tsetse flies

Spatio-temporally heterogeneous environments may lead to unexpected population dynamics. Knowledge is needed on local properties favouring population resilience at large scale. For pathogen vectors, such as tsetse flies transmitting human and animal African trypanosomosis, this is crucial to target management strategies. We developed a mechanistic spatio-temporal model of the age-structured population dynamics of tsetse flies, parametrized with field and laboratory data. It accounts for density- and temperature-dependence. The studied environment is heterogeneous, fragmented and dispersal is suitability-driven. We confirmed that temperature and adult mortality have a strong impact on tsetse populations. When homogeneously increasing adult mortality, control was less effective and induced faster population recovery in the coldest and temperature-stable locations, creating refuges. To optimally select locations to control, we assessed the potential impact of treating them and their contribution to the whole population. This heterogeneous control induced a similar population decrease, with more dispersed individuals. Control efficacy was no longer related to temperature. Dispersal was responsible for refuges at the interface between controlled and uncontrolled zones, where resurgence after control was very high. The early identification of refuges, which could jeopardize control efforts, is crucial. We recommend baseline data collection to characterize the ecosystem before implementing any measures.

Insights into the Control and Management of Human and Bovine African Trypanosomiasis in Zambia between 2009 and 2019-A Review

Tsetse transmitted trypanosomiasis is a fatal disease commonly known as Nagana in cattle and sleeping sickness in humans. The disease threatens food security and has severe economic impact in Africa including most parts of Zambia. The level of effectiveness of commonly used African trypanosomiasis control methods has been reported in several studies. However, there have been no review studies on African trypanosomiasis control and management conducted in the context of One Health. This paper therefore seeks to fill this knowledge gap. A review of studies that have been conducted on African trypanosomiasis in Zambia between 2009 and 2019, with a focus on the control and management of trypanosomiasis was conducted. A total of 2238 articles were screened, with application of the search engines PubMed, PubMed Central and One Search. Out of these articles, 18 matched the required criteria and constituted the basis for the paper. An in-depth analysis of the 18 articles was conducted to identify knowledge gaps and evidence for best practices. Findings from this review provide stakeholders and health workers with a basis for prioritisation of African trypanosomiasis as an important neglected disease in Zambia and for formulation of One Health strategies for better control and/or management of the disease.

Models for the rates of pupal development, fat consumption and mortality in tsetse (Glossina spp)

Environmental temperature is an important driver of the population dynamics of tsetse (Glossina spp) because the fly's immature stages are particularly vulnerable to temperatures (T) outside the range T = 16-32°C. Laboratory experiments carried out 50 years ago provide extensive measures of temperature-dependent rates of development, fat consumption and mortality in tsetse pupae. We improve on the models originally fitted to these data, providing better parameter estimates for use in population modelling. A composite function accurately models rates of pupal development for T = 8-32°C. Pupal duration can be estimated by summing the temperature-dependent daily percentage of development completed. Fat consumption is modelled as a logistic function of temperature; the total fat consumed during pupal development takes a minimum for T ≈ 25°C. Pupae experiencing constant temperatures <16°C exhaust their fat reserves before they complete development. At high temperatures, direct effects kill the pupae before fat stores are exhausted. The relationship between pupal mortality and temperature is well described by the sum of two exponential functions. Summing daily mortality rates over the whole pupal period does not reliably predict overall mortality. Mortality is more strongly correlated with the mean temperature experienced over pupal life or, for T ≤ 30°C, the fat consumption during this period. The new results will be particularly useful in the construction of various models for tsetse population dynamics, and will have particular relevance for agent-based models where the lives of individual tsetse are simulated using a daily time step.

Exploring the effect of human and animal population growth on vector-borne disease transmission with an agent-based model of Rhodesian human African trypanosomiasis in eastern province, Zambia

This paper presents the development of an agent-based model (ABM) to investigate Trypanosoma brucei rhodesiense human African trypanosomiasis (rHAT) disease transmission. The ABM model, fitted at a fine spatial scale, was used to explore the impact of a growing host population on the spread of disease along a 75 km transect in the Luangwa Valley, Zambia. The model was used to gain a greater understanding of how increases in human and domestic animal population could impact the contact network between vector and host, the subsequent transmission patterns, and disease incidence outcomes in the region. Modelled incidence rates showed increases in rHAT transmission in both humans and cattle. The primary demographic attribution of infection switched dramatically from young children of both sexes attending school, to adult women performing activities with shorter but more frequent trips, such as water and firewood collection, with men more protected due to the presence of cattle in their routines. The interpretation of model output provides a plausible insight into both population development and disease transmission in the near future in the region and such techniques could aid well-targeted mitigation strategies in the future.

African trypanosomiasis is a parasitic disease which affects humans and other animals in 36 sub-Saharan African countries. The disease is transmitted by the tsetse fly, and the human form of the disease is known as sleeping sickness. With human and animal populations growing across Africa, demand for space to settle is on the rise, and people are being forced to occupy increasingly marginal spaces. This behaviour has the potential to increase exposure to pre-existing biological hazards, including vector-borne diseases. This investigation utilises agent-based modelling techniques to investigate the implications of a growing and spreading human and animal population in a region affected by Rhodesian human African trypanosomiasis. The model incorporates previously developed spatial data for the Luangwa Valley case study in Zambia, along with demographic data for its current inhabitants, and a detailed, seasonally-driven tsetse lifecycle. Tsetse and potential human and animal hosts are modelled at the individual level, allowing each contact and infection to be recorded through time. By modelling at a fine-scale, we can incorporate detailed mechanisms for tsetse birth, feeding, reproduction and death, as well as a realistic theoretical human and domestic animal population increase, before considering the possible spatial and demographic impact.

An agent-based model of tsetse fly response to seasonal climatic drivers: Assessing the impact on sleeping sickness transmission rates

BACKGROUND

This paper presents the development of an agent-based model (ABM) to incorporate climatic drivers which affect tsetse fly (G. m. morsitans) population dynamics, and ultimately disease transmission. The model was used to gain a greater understanding of how tsetse populations fluctuate seasonally, and investigate any response observed in Trypanosoma brucei rhodesiense human African trypanosomiasis (rHAT) disease transmission, with a view to gaining a greater understanding of disease dynamics. Such an understanding is essential for the development of appropriate, well-targeted mitigation strategies in the future.

METHODS

The ABM was developed to model rHAT incidence at a fine spatial scale along a 75 km transect in the Luangwa Valley, Zambia. The model incorporates climatic factors that affect pupal mortality, pupal development, birth rate, and death rate. In combination with fine scale demographic data such as ethnicity, age and gender for the human population in the region, as well as an animal census and a sample of daily routines, we create a detailed, plausible simulation model to explore tsetse population and disease transmission dynamics.

RESULTS

The seasonally-driven model suggests that the number of infections reported annually in the simulation is likely to be a reasonable representation of reality, taking into account the high levels of under-detection observed. Similar infection rates were observed in human (0.355 per 1000 person-years (SE = 0.013)), and cattle (0.281 per 1000 cattle-years (SE = 0.025)) populations, likely due to the sparsity of cattle close to the tsetse interface. The model suggests that immigrant tribes and school children are at greatest risk of infection, a result that derives from the bottom-up nature of the ABM and conditioning on multiple constraints. This result could not be inferred using alternative population-level modelling approaches.

CONCLUSIONS

In producing a model which models the tsetse population at a very fine resolution, we were able to analyse and evaluate specific elements of the output, such as pupal development and the progression of the teneral population, allowing the development of our understanding of the tsetse population as a whole. This is an important step in the production of a more accurate transmission model for rHAT which can, in turn, help us to gain a greater understanding of the transmission system as a whole.