A Comparison of Markov and Mechanistic Models for Soil-Transmitted Helminth Prevalence Projections in the Context of Survey Design.

Globally, there are over 1 billion people infected with soil-transmitted helminths (STHs), mostly living in marginalized settings with inadequate sanitation in sub-Saharan Africa and Southeast Asia. The World Health Organization recommends an integrated approach to STH morbidity control through improved access to sanitation and hygiene education and the delivery of preventive chemotherapy (PC) to school-age children delivered through schools. Progress of STH control programs is currently estimated using a baseline (pre-PC) school-based prevalence survey and then monitored using periodical school-based prevalence surveys, known as Impact Assessment Surveys (IAS). We investigated whether integrating geostatistical methods with a Markov model or a mechanistic transmission model for projecting prevalence forward in time from baseline can improve IAS design strategies. To do this, we applied these 2 methods to prevalence data collected in Kenya, before evaluating and comparing their performance in accurately informing optimal survey design for a range of IAS sampling designs. We found that, although both approaches performed well, the mechanistic method more accurately projected prevalence over time and provided more accurate information for guiding survey design. Both methods performed less well in areas with persistent STH hotspots where prevalence did not decrease despite multiple rounds of PC. Our findings show that these methods can be useful tools for more efficient and accurate targeting of PC. The general framework built in this paper can also be used for projecting prevalence and informing survey design for other neglected tropical diseases.

Gender differences in the perception of leptospirosis severity, behaviours, and Leptospira exposure risk in urban Brazil: a cross-sectional study.

Background: Vulnerability to climate hazards and infectious diseases are not gender-neutral, meaning that men, women, boys, girls, and other gender identities experience different health risks. Leptospirosis, a zoonotic climate sensitive infectious disease, is commonly transmitted to humans via contact with animals and the environment, particularly soil and flood water. Gender differences in leptospiral infection risk are reported globally, with men consistently found to be at higher risk than women. However, the drivers of this difference in risk are poorly understood. Previous studies suggest that the interplay of knowledge, perceptions, and behaviours may shape differential infection risk among genders. Methodology/Principal Findings: To examine gender differences in Leptospira exposure risk we conducted a cross-sectional serosurvey among adult participants (n = 761) in four urban, marginalised, informal settlements in the city of Salvador, Brazil. We found that seroprevalence was 14.6% and 9.4% across men and women respectively. We then applied causal inference methodology to a two-part sex-disaggregated analysis to investigate: 1) the association of perceptions and behaviours with Leptospira seropositivity and 2) the association of perceptions with behaviours. We found that men who perceived leptospirosis as extremely serious had lower odds of seropositivity, walking through sewage water, or walking barefoot, suggesting an important link between perceptions, behaviours, and exposure risk. These associations were not found in women, and these behaviours were not associated with seropositivity in men or women. Conclusions: Our results highlight perceived severity of disease as a potential driver of behaviour in men, and perceptions of disease may be an important target for health education programs. Furthermore, our study identifies evidence gaps in the understanding of infection risks in women. As the first sex-disaggregated study investigating Leptospira infection risks, we advocate for a gendered lens in future studies to further understand risks specific to different gender identities.

Household overcrowding and risk of SARS-CoV-2: analysis of the Virus Watch prospective community cohort study in England and Wales.

Background: Household overcrowding is associated with increased risk of infectious diseases across contexts and countries. Limited data exist linking household overcrowding and risk of COVID-19. We used data collected from the Virus Watch cohort to examine the association between overcrowded households and SARS-CoV-2. Methods: The Virus Watch study is a household community cohort of acute respiratory infections in England and Wales. We calculated overcrowding using the measure of persons per room for each household. We considered two primary outcomes: PCR-confirmed positive SARS-CoV-2 antigen tests and laboratory-confirmed SARS-CoV-2 antibodies. We used mixed-effects logistic regression models that accounted for household structure to estimate the association between household overcrowding and SARS-CoV-2 infection. Results:26,367 participants were included in our analyses. The proportion of participants with a positive SARS-CoV-2 PCR result was highest in the overcrowded group (9.0%; 99/1,100) and lowest in the under-occupied group (4.2%; 980/23,196). In a mixed-effects logistic regression model, we found strong evidence of an increased odds of a positive PCR SARS-CoV-2 antigen result (odds ratio 2.45; 95% CI:1.43-4.19; p-value=0.001) and increased odds of a positive SARS-CoV-2 antibody result in individuals living in overcrowded houses (3.32; 95% CI:1.54-7.15; p-value<0.001) compared with people living in under-occupied houses. Conclusion:Public health interventions to prevent and stop the spread of SARS-CoV-2 should consider the risk of infection for people living in overcrowded households and pay greater attention to reducing household transmission.