The Effect of Simulating Different Intermediate Host Snail Species on the Link between Water Temperature and Schistosomiasis Risk

Introduction: A number of studies have attempted to predict the effects of climate change on schistosomiasis risk. The importance of considering different species of intermediate host snails separately has never previously been explored. Methods: An agent-based model of water temperature and Biomphalaria pfeifferi population dynamics and Schistosoma mansoni transmission was parameterised to two additional species of snail: B. glabrata and B. alexandrina. Results: Simulated B. alexandrina populations had lower minimum and maximum temperatures for survival than B. pfeifferi populations (12.5–29.5°C vs. 14.0–31.5°C). B. glabrata populations survived over a smaller range of temperatures than either B. pfeifferi or B. alexandrina (17.0°C–29.5°C). Infection risk peaked at 16.5°C, 25.0°C and 19.0°C respectively when B. pfeifferi, B. glabrata and B. alexandrina were simulated. For all species, infection risk increased sharply once a minimum temperature was reached. Conclusions: The results from all three species suggest that infection risk may increase dramatically with small increases in temperature in areas at or near the currents limits of schistosome transmission. The effect of small increases in temperature in areas where schistosomiasis is currently found will depend both on current temperatures and on the species of snail acting as intermediate host(s) in the area. In most areas where B. pfeifferi is the host, infection risk is likely to decrease. In cooler areas where B. glabrata is the host, infection risk may increase slightly. In cooler areas where B. alexandrina is the host, infection risk may more than double with only 2°C increase in temperature. Our results show that it is crucial to consider the species of intermediate host when attempting to predict the effects of climate change on schistosomiasis

Predicting the effects of climate change on Schistosoma mansoni transmission in eastern Africa

Background: Survival and fitness attributes of free-living and sporocyst schistosome life-stages and their intermediate host snails are sensitive to water temperature. Climate change may alter the geographical distribution of schistosomiasis by affecting the suitability of freshwater bodies for hosting parasite and snail populations. Methods: We have developed an agent-based model of the temperature-sensitive stages of the Schistosoma mansoni and intermediate host snail lifecycles. The model was run using low, moderate and high warming climate projections over eastern Africa. For each climate projection, eight model scenarios were used to determine the sensitivity of predictions to different relationships between air and water temperature, and different snail mortality rates. Maps were produced showing predicted changes in risk as a result of increasing temperatures over the next 20 and 50 years. Results Baseline model output compared to prevalence data indicates suitable temperatures are necessary but not sufficient for both S. mansoni transmission and high infection prevalences. All else being equal, infection risk may increase by up to 20% over most of eastern Africa over the next 20 and 50 years. Increases may be higher in Rwanda, Burundi, south-west Kenya and eastern Zambia, and S. mansoni may become newly endemic in some areas. Results for 20-year projections are robust to changes in simulated intermediate host snail habitat conditions. There is greater uncertainty about the effects of different habitats on changes in risk in 50 years’ time. Conclusions: Temperatures are likely to become suitable for increased S. mansoni transmission over much of eastern Africa. This may reduce the impact of control and elimination programmes. S. mansoni may also spread to new areas outside existing control programmes. We call for increased surveillance in areas defined as potentially suitable for emergent transmission

Efficient History Matching of a High Dimensional Individual-Based HIV Transmission Model

History matching is a model (pre-)calibration method that has been applied to computer models from a wide range of scientific disciplines. In this work we apply history matching to an individual-based epidemiological model of HIV that has 96 input and 50 output parameters, a model of much larger scale than others that have been calibrated before using this or similar methods. Apart from demonstrating that history matching can analyze models of this complexity, a central contribution of this work is that the history match is carried out using linear regression, a statistical tool that is elementary and easier to implement than the Gaussian process--based emulators that have previously been used. Furthermore, we address a practical difficulty with history matching, namely, the sampling of tiny, nonimplausible spaces, by introducing a sampling algorithm adjusted to the specific needs of this method. The effectiveness and simplicity of the history matching method presented here shows that it is a useful tool for the calibration of computationally expensive, high dimensional, individual-based models

Bayesian history matching of complex infectious disease models using emulation: A tutorial and a case study on HIV in Uganda

Advances in scientific computing have allowed the development of complex models that are being routinely applied to problems in disease epidemiology, public health and decision making. The utility of these models depends in part on how well they can reproduce empirical data. However, fitting such models to real world data is greatly hindered both by large numbers of input and output parameters, and by long run times, such that many modelling studies lack a formal calibration methodology. We present a novel method that has the potential to improve the calibration of complex infectious disease models (hereafter called simulators). We present this in the form of a tutorial and a case study where we history match a dynamic, event-driven, individual-based stochastic HIV simulator, using extensive demographic, behavioural and epidemiological data available from Uganda. The tutorial describes history matching and emulation. History matching is an iterative procedure that reduces the simulator's input space by identifying and discarding areas that are unlikely to provide a good match to the empirical data. History matching relies on the computational efficiency of a Bayesian representation of the simulator, known as an emulator. Emulators mimic the simulator's behaviour, but are often several orders of magnitude faster to evaluate. In the case study, we use a 22 input simulator, fitting its 18 outputs simultaneously. After 9 iterations of history matching, a non-implausible region of the simulator input space was identified that was times smaller than the original input space. Simulator evaluations made within this region were found to have a 65% probability of fitting all 18 outputs. History matching and emulation are useful additions to the toolbox of infectious disease modellers. Further research is required to explicitly address the stochastic nature of the simulator as well as to account for correlations between outputs

Importance of ventilation and occupancy to Mycobacterium tuberculosis transmission rates in congregate settings

BACKGROUND: Ventilation rates are a key determinant of the transmission rate of Mycobacterium tuberculosis and other airborne infections. Targeting infection prevention and control (IPC) interventions at locations where ventilation rates are low and occupancy high could be a highly effective intervention strategy. Despite this, few data are available on ventilation rates and occupancy in congregate locations in high tuberculosis burden settings. METHODS: We collected carbon dioxide concentration and occupancy data in congregate locations and public transport on 88 occasions, in Cape Town, South Africa. For each location, we estimated ventilation rates and the relative rate of infection, accounting for ventilation rates and occupancy. RESULTS: We show that the estimated potential transmission rate in congregate settings and public transport varies greatly between different settings. Overall, in the community we studied, estimated infection risk was higher in minibus taxis and trains than in salons, bars, and shops. Despite good levels of ventilation, infection risk could be high in the clinic due to high occupancy levels. CONCLUSION: Public transport in particular may be promising targets for infection prevention and control interventions in this setting, both to reduce Mtb transmission, but also to reduce the transmission of other airborne pathogens such as measles and SARS-CoV-2

Tuberculosis from transmission in clinics in high HIV settings may be far higher than contact data suggest.

BACKGROUND: In South Africa, it is generally estimated that only 0.5-0.6% of people's contacts occur in clinics. Both people with infectious tuberculosis and people with increased susceptibility to disease progression may spend more time in clinics, however, increasing the importance of clinic-based transmission to overall disease incidence.METHODS: We developed an illustrative mathematical model of Mycobacterium tuberculosis transmission in clinics and other settings. We assumed that 1% of contact time occurs in clinics. We varied the ratio of clinic contact time of human immunodeficiency virus (HIV) positive people compared to HIV-negative people, and of people with infectious TB compared to people without TB, while keeping the overall proportion of contact time occurring in clinics, and each person's total contact time, constant.RESULTS: With clinic contact rates respectively 10 and 5 times higher in HIV-positive people and people with TB, 10.7% (plausible range 8.5-13.4%) of TB resulted from transmission in clinics. With contact rates in HIV-positive people and people with TB respectively 5 and 2 times higher, 5.3% (plausible range 4.3-6.3%) of all TB was due to transmission in clinics.CONCLUSION: The small amount of contact time that generally occurs in clinics may greatly underestimate their contribution to TB disease in high TB-HIV burden settings

Coverage of clinic-based TB screening in South Africa may be low in key risk groups

The South African Ministry of Health has proposed screening all clinic attendees for tuberculosis (TB). Amongst other factors, male sex and bar attendance are associated with higher TB risk. We show that 45% of adults surveyed in Western Cape attended a clinic within 6 months, and therefore potentially a relatively high proportion of the population could be reached through clinic-based screening. However, fewer than 20% of all men aged 18–25 years, or men aged 26–45 who attend bars, attended a clinic. The population-level impact of clinic-based screening may be reduced by low coverage among key risk groups

Improving ART programme retention and viral suppression are key to maximising impact of treatment as prevention - a modelling study.

BACKGROUND: UNAIDS calls for fewer than 500,000 new HIV infections/year by 2020, with treatment-as-prevention being a key part of their strategy for achieving the target. A better understanding of the contribution to transmission of people at different stages of the care pathway can help focus intervention services at populations where they may have the greatest effect. We investigate this using Uganda as a case study. METHODS: An individual-based HIV/ART model was fitted using history matching. 100 model fits were generated to account for uncertainties in sexual behaviour, HIV epidemiology, and ART coverage up to 2015 in Uganda. A number of different ART scale-up intervention scenarios were simulated between 2016 and 2030. The incidence and proportion of transmission over time from people with primary infection, post-primary ART-naïve infection, and people currently or previously on ART was calculated. RESULTS: In all scenarios, the proportion of transmission by ART-naïve people decreases, from 70% (61%-79%) in 2015 to between 23% (15%-40%) and 47% (35%-61%) in 2030. The proportion of transmission by people on ART increases from 7.8% (3.5%-13%) to between 14% (7.0%-24%) and 38% (21%-55%). The proportion of transmission by ART dropouts increases from 22% (15%-33%) to between 31% (23%-43%) and 56% (43%-70%). CONCLUSIONS: People who are currently or previously on ART are likely to play an increasingly large role in transmission as ART coverage increases in Uganda. Improving retention on ART, and ensuring that people on ART remain virally suppressed, will be key in reducing HIV incidence in Uganda

The general population cohort in rural south-western Uganda: a platform for communicable and non-communicable disease studies.

The General Population Cohort (GPC) was set up in 1989 to examine trends in HIV prevalence and incidence, and their determinants in rural south-western Uganda. Recently, the research questions have included the epidemiology and genetics of communicable and non-communicable diseases (NCDs) to address the limited data on the burden and risk factors for NCDs in sub-Saharan Africa. The cohort comprises all residents (52% aged ≥13years, men and women in equal proportions) within one-half of a rural sub-county, residing in scattered houses, and largely farmers of three major ethnic groups. Data collected through annual surveys include; mapping for spatial analysis and participant location; census for individual socio-demographic and household socioeconomic status assessment; and a medical survey for health, lifestyle and biophysical and blood measurements to ascertain disease outcomes and risk factors for selected participants. This cohort offers a rich platform to investigate the interplay between communicable diseases and NCDs. There is robust infrastructure for data management, sample processing and storage, and diverse expertise in epidemiology, social and basic sciences. For any data access enquiries you may contact the director, MRC/UVRI, Uganda Research Unit on AIDS by email to [email protected] or the corresponding author