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

An Agent-Based Model of Biting Midge Dynamics to Understand Bluetongue Outbreaks

Bluetongue (BT) is a well-known vector-borne disease that infects ruminants such as sheep, cattle, and deer with high mortality rates. Recent outbreaks in Europe highlight the importance of understanding vector-host dynamics and potential courses of action to mitigate the damage that can be done by BT. We present an agent-based model, entitled 'MidgePy', that focuses on the movement of individual Culicoides spp. biting midges and their interactions with ruminants to understand their role as vectors in BT outbreaks, especially in regions that do not regularly experience outbreaks. The results of our sensitivity analysis suggest that midge survival rate has a significant impact on the probability of a BTV outbreak as well as its severity. Using midge flight activity as a proxy for temperature, we found that an increase in environmental temperature corresponded with an increased probability of outbreak after identifying parameter regions where outbreaks are more likely to occur. This suggests that future methods to control BT spread could combine large-scale vaccination programs with biting midge population control measures such as the use of pesticides. Spatial heterogeneity in the environment is also explored to give insight on optimal farm layouts to reduce the potential for BT outbreaks.

Exploring N-myristoyltransferase as a promising drug target against parasitic neglected tropical diseases

Neglected tropical diseases (NTDs) constitute a group of approximately 20 infectious diseases that mainly affect the impoverished population without basic sanitation in tropical countries. These diseases are responsible for many deaths worldwide, costing billions of dollars in public health investment to treat and control these infections. Among them are the diseases caused by protozoa of the Trypanosomatid family, which constitute Trypanosoma cruzi (Chagas disease), Trypanosoma brucei (sleeping sickness), and Leishmaniasis. In addition, there is a classification of other diseases, called the big three, AIDS, tuberculosis, and malaria, which are endemic in countries with tropical conditions. Despite the high mortality rates, there is still a gap in the treatment. The drugs have a high incidence of side effects and protozoan resistance, justifying the investment in developing new alternatives. In fact, the Target-Based Drug Design (TBDD) approach is responsible for identifying several promising compounds, and among the targets explored through this approach, N-myristoyltransferase (NMT) stands out. It is an enzyme related to the co-translational myristoylation of N-terminal glycine in various peptides. The myristoylation process is a co-translation that occurs after removing the initiator methionine. This process regulates the assembly of protein complexes and stability, which justifies its potential as a drug target. In order to propose NMT as a potential target for parasitic diseases, this review will address the entire structure and function of this enzyme and the primary studies demonstrating its promising potential against Leishmaniasis, T. cruzi, T. brucei, and malaria. We hope our information can help researchers worldwide search for potential drugs against these diseases that have been threatening the health of the world's population.

Projecting the Potential Distribution of Glossinamorsitans (Diptera: Glossinidae) under Climate Change Using the MaxEnt Model

Simple Summary

Glossina morsitans is a species of tsetse flies and a vector for Human African Trypanosomiasis, which is a severe parasitic infectious illness that can lead to death unless treated. At present, the G. morsitans are mainly found in sub-Saharan Africa. But modifications of its distribution undergoing as a result of climate change is still unknown. In order to provide scientific basis for effective monitoring and G. morsitans control, this study aimed to collect the distribution and to explore the potentially suitable habitat for G. morsitans under various scenarios. We downloaded the major data of G. morsitans occurrence from the Global Biodiversity Information Facility. Maxent software and R language were employed to analyze the relationship between occurrence records and climatic variables and project the potentially suitable habitat for G. morsitans in historical and future periods. The results showed that Isothermality contributed most to the distribution of G. morsitans. The predicted potentially suitable areas for G. morsitans under historical climate conditions include a large area of Africa near and below the equator, small equatorial regions of southern Asia, America, and Oceania. Under the future climate conditions, the potentially suitable areas would decline about −5.38 ± 1.00% as a whole under all SSPs compared with 1970–2000.

Abstract

Glossina morsitans is a vector for Human African Trypanosomiasis (HAT), which is mainly distributed in sub-Saharan Africa at present. Our objective was to project the historical and future potentially suitable areas globally and explore the influence of climatic factors. The maximum entropy model (MaxEnt) was utilized to evaluate the contribution rates of bio-climatic factors and to project suitable habitats for G. morsitans. We found that Isothermality and Precipitation of Wettest Quarter contributed most to the distribution of G. morsitans. The predicted potentially suitable areas for G. morsitans under historical climate conditions would be 14.5 million km², including a large area of Africa which is near and below the equator, small equatorial regions of southern Asia, America, and Oceania. Under future climate conditions, the potentially suitable areas are expected to decline by about −5.38 ± 1.00% overall, under all shared socioeconomic pathways, compared with 1970–2000. The potentially suitable habitats of G. morsitans may not be limited to Africa. Necessary surveillance and preventive measures should be taken in high-risk regions.

The impact of climate change on neglected tropical diseases: a systematic review

Neglected tropical diseases (NTDs) are a diverse group of diseases that continue to affect >1 billion people, with these diseases disproportionately impacting vulnerable populations and territories. Climate change is having an increasing impact on public health in tropical and subtropical areas and across the world and can affect disease distribution and transmission in potentially diverse ways. Improving our understanding of how climate change influences NTDs can help identify populations at risk to include in future public health interventions. Articles were identified by searching electronic databases for reports of climate change and NTDs between 1 January 2010 and 1 March 2020. Climate change may influence the emergence and re-emergence of multiple NTDs, particularly those that involve a vector or intermediate host for transmission. Although specific predictions are conflicting depending on the geographic area, the type of NTD and associated vectors and hosts, it is anticipated that multiple NTDs will have changes in their transmission period and geographic range and will likely encroach on regions and populations that have been previously unaffected. There is a need for improved surveillance and monitoring to identify areas of NTD incursion and emergence and include these in future public health interventions.

Epidemiology of Trypanosomiasis in Wildlife-Implications for Humans at the Wildlife Interface in Africa

While both human and animal trypanosomiasis continue to present as major human and animal public health constraints globally, detailed analyses of trypanosome wildlife reservoir hosts remain sparse. African animal trypanosomiasis (AAT) affects both livestock and wildlife carrying a significant risk of spillover and cross-transmission of species and strains between populations. Increased human activity together with pressure on land resources is increasing wildlife–livestock–human infections. Increasing proximity between human settlements and grazing lands to wildlife reserves and game parks only serves to exacerbate zoonotic risk. Communities living and maintaining livestock on the fringes of wildlife-rich ecosystems require to have in place methods of vector control for prevention of AAT transmission and for the treatment of their livestock. Major Trypanosoma spp. include Trypanosoma brucei rhodesiense, Trypanosoma brucei gambiense, and Trypanosoma cruzi, pathogenic for humans, and Trypanosoma vivax, Trypanosoma congolense, Trypanosoma evansi, Trypanosoma brucei brucei, Trypanosoma dionisii, Trypanosoma thomasbancrofti, Trypanosma elephantis, Trypanosoma vegrandis, Trypanosoma copemani, Trypanosoma irwini, Trypanosoma copemani, Trypanosoma gilletti, Trypanosoma theileri, Trypanosoma godfreyi, Trypansoma simiae, and Trypanosoma (Megatrypanum) pestanai. Wildlife hosts for the trypansomatidae include subfamilies of Bovinae, Suidae, Pantherinae, Equidae, Alcephinae, Cercopithecinae, Crocodilinae, Pteropodidae, Peramelidae, Sigmodontidae, and Meliphagidae. Wildlife species are generally considered tolerant to trypanosome infection following centuries of coexistence of vectors and wildlife hosts. Tolerance is influenced by age, sex, species, and physiological condition and parasite challenge. Cyclic transmission through Glossina species occurs for T. congolense, T. simiae, T. vivax, T. brucei, and T. b. rhodesiense, T. b. gambiense, and within Reduviid bugs for T. cruzi. T. evansi is mechanically transmitted, and T. vixax is also commonly transmitted by biting flies including tsetse. Wildlife animal species serve as long-term reservoirs of infection, but the delicate acquired balance between trypanotolerance and trypanosome challenge can be disrupted by an increase in challenge and/or the introduction of new more virulent species into the ecosystem. There is a need to protect wildlife, animal, and human populations from the infectious consequences of encroachment to preserve and protect these populations. In this review, we explore the ecology and epidemiology of Trypanosoma spp. in wildlife.

Mathematical modelling and control of African animal trypanosomosis with interacting populations in West Africa-Could biting flies be important in main taining the disease endemicity?

African animal trypanosomosis (AAT) is transmitted cyclically by tsetse flies and mechanically by biting flies (tabanids and stomoxyines) in West Africa. AAT caused by Trypanosoma congolense, T. vivax and T. brucei brucei is a major threat to the cattle industry. A mathematical model involving three vertebrate hosts (cattle, small ruminants and wildlife) and three vector flies (Tsetse flies, tabanids and stomoxyines) was described to identify elimination strategies. The basic reproduction number (R₀) was obtained with respect to the growth rate of infected wildlife (reservoir hosts) present around the susceptible population using a next generation matrix technique. With the aid of suitable Lyapunov functions, stability analyses of disease-free and endemic equilibria were established. Simulation of the predictive model was presented by solving the system of ordinary differential equations to explore the behaviour of the model. An operational area in southwest Nigeria was simulated using generated pertinent data. The R₀ < 1 in the formulated model indicates the elimination of AAT. The comprehensive use of insecticide treated targets and insecticide treated cattle (ITT/ITC) affected the feeding tsetse and other biting flies resulting in R₀ < 1. The insecticide type, application timing and method, expertise and environmental conditions could affect the model stability. In areas with abundant biting flies and no tsetse flies, T. vivax showed R₀ > 1 when infected wildlife hosts were present. High tsetse populations revealed R₀ <1 for T. vivax when ITT and ITC were administered, either individually or together. Elimination of the transmitting vectors of AAT could cost a total of US$ 1,056,990 in southwest Nigeria. Hence, AAT in West Africa can only be controlled by strategically applying insecticides targeting all transmitting vectors, appropriate use of trypanocides, and institutionalising an appropriate barrier between the domestic and sylvatic areas.

Uncertainty and sensitivity analyses of extinction probabilities suggest that adult female mortality is the weakest link for populations of tsetse (Glossina spp)

Background

A relatively simple life history allows us to derive an expression for the extinction probability of populations of tsetse, vectors of African sleeping sickness. We present the uncertainty and sensitivity analysis of the extinction probability, to offer key insights into factors affecting the control or eradication of tsetse populations.

Methods

We represent tsetse population growth as a branching process, and derive closed form estimates of population extinction from that model. Statistical and mathematical techniques are used to analyse the uncertainties in estimating extinction probability, and the sensitivity of the extinction probability to changes in input parameters representing the natural life history and vital dynamics of tsetse populations.

Results

For fixed values of input parameters, the sensitivity of extinction probability depends on the baseline parameter values. Extinction probability is most sensitive to the probability that a female is inseminated by a fertile male when daily pupal mortality is low, whereas the extinction probability is most sensitive to daily mortality rate for adult females when daily pupal mortality, and extinction probabilities, are high. Global uncertainty and sensitivity analysis show that daily mortality rate for adult females has the highest impact on the extinction probability.

Conclusions

The high correlation between extinction probability and daily female adult mortality gives a strong argument that control techniques which increase daily female adult mortality may be the single most effective means of ensuring eradication of tsetse population.

Tsetse flies (Glossina spp.) are vectors of African trypanosomiasis, a deadly disease commonly called sleeping sickness in humans and nagana in livestock. The relatively simple life history of tsetse enabled us to model its population growth as a stochastic branching process. We derived a closed-form expression for the probability that a population of tsetse goes extinct, as a function of death, birth, development and insemination rates in female tsetse. We analyzed the sensitivity of the extinction probability to the different input parameters, in a bid to identify parameters with the highest impact on extinction probability. This information can, potentially, inform policy direction for tsetse control/elimination. In all the scenarios we considered for the global sensitivity analysis, the daily mortality rate for adult females had the greatest impact on the magnitude of extinction probability. Our findings suggest that the mortality rate in the adult females is the weakest link in tsetse life history, and this fact should be exploited in achieving tsetse population control, or even eradication.

Estimating tsetse fertility: daily averaging versus periodic larviposition

When computing mean daily fertility in adult female tsetse, the common practice of taking the reciprocal of the interlarval period (called averaged fertility) was compared with the method of taking the sum of the products of daily fertility and adult survivorship divided by the sum of daily survivorships (called periodic fertility). The latter method yielded a consistently higher measure of fertility (approximately 10% for tsetse) than the former method. A conversion factor was calculated to convert averaged fertility to periodic fertility. A feasibility criterion was determined for the viability of a tsetse population. Fertility and survivorship data from tsetse populations on Antelope Is. and Redcliff Is., both in Zimbabwe, were used to illustrate the feasibility criterion, as well as the limitations imposed by survivorship and fertility on the viability of tsetse populations. The 10% difference in fertility between the two methods of calculation makes the computation of population feasibility with some parameter combinations sometimes result in a wrong answer. It also underestimates both sterile male release rates required to eradicate a pest population, as well as the speed of resurgence if an eradication attempt fails.

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.