Species distribution modeling for disease ecology: A multi-scale case study for schistosomiasis host snails in Brazil.

Species distribution models (SDMs) are increasingly popular tools for profiling disease risk in ecology, particularly for infectious diseases of public health importance that include an obligate non-human host in their transmission cycle. SDMs can create high-resolution maps of host distribution across geographical scales, reflecting baseline risk of disease. However, as SDM computational methods have rapidly expanded, there are many outstanding methodological questions. Here we address key questions about SDM application, using schistosomiasis risk in Brazil as a case study. Schistosomiasis is transmitted to humans through contact with the free-living infectious stage of Schistosoma spp. parasites released from freshwater snails, the parasite's obligate intermediate hosts. In this study, we compared snail SDM performance across machine learning (ML) approaches (MaxEnt, Random Forest, and Boosted Regression Trees), geographic extents (national, regional, and state), types of presence data (expert-collected and publicly-available), and snail species (Biomphalaria glabrata, B. straminea, and B. tenagophila). We used high-resolution (1km) climate, hydrology, land-use/land-cover (LULC), and soil property data to describe the snails' ecological niche and evaluated models on multiple criteria. Although all ML approaches produced comparable spatially cross-validated performance metrics, their suitability maps showed major qualitative differences that required validation based on local expert knowledge. Additionally, our findings revealed varying importance of LULC and bioclimatic variables for different snail species at different spatial scales. Finally, we found that models using publicly-available data predicted snail distribution with comparable AUC values to models using expert-collected data. This work serves as an instructional guide to SDM methods that can be applied to a range of vector-borne and zoonotic diseases. In addition, it advances our understanding of the relevant environment and bioclimatic determinants of schistosomiasis risk in Brazil.

Climate and urbanization drive changes in the habitat suitability of Schistosoma mansoni competent snails in Brazil.

Schistosomiasis is a neglected tropical disease caused by Schistosoma parasites. Schistosoma are obligate parasites of freshwater Biomphalaria and Bulinus snails, thus controlling snail populations is critical to reducing transmission risk. As snails are sensitive to environmental conditions, we expect their distribution is significantly impacted by global change. Here, we used machine learning, remote sensing, and 30 years of snail occurrence records to map the historical and current distribution of forward-transmitting Biomphalaria hosts throughout Brazil. We identified key features influencing the distribution of suitable habitat and determined how Biomphalaria habitat has changed with climate and urbanization over the last three decades. Our models show that climate change has driven broad shifts in snail host range, whereas expansion of urban and peri-urban areas has driven localized increases in habitat suitability. Elucidating change in Biomphalaria distribution-while accounting for non-linearities that are difficult to detect from local case studies-can help inform schistosomiasis control strategies.

Estimates of SARS-CoV-2 Hospitalization and Fatality Rates in the Prevaccination Period, United States.

Few precise estimates of hospitalization and fatality rates from COVID-19 exist for naive populations, especially within demographic subgroups. We estimated rates among persons with SARS-CoV-2 infection in the United States during May 1-December 1, 2020, before vaccines became available. Both rates generally increased with age; fatality rates were highest for persons >85 years of age (24%) and lowest for children 1-14 years of age (0.01%). Age-adjusted case hospitalization rates were highest for African American or Black, not Hispanic persons (14%), and case-fatality rates were highest for Asian or Pacific Islander, not Hispanic persons (4.4%). Eighteen percent of hospitalized patients and 44.2% of those admitted to an intensive care unit died. Male patients had higher hospitalization (6.2% vs. 5.2%) and fatality rates (1.9% vs. 1.5%) than female patients. These findings highlight the importance of collecting surveillance data to devise appropriate control measures for persons in underserved racial/ethnic groups and older adults.

Climate and urbanization drive changes in the habitat suitability of Schistosoma mansoni competent snails in Brazil.

Schistosomiasis is a neglected tropical disease caused by Schistosoma parasites. Schistosoma are obligate parasites of freshwater Biomphalaria snails, so controlling snail populations is critical to reducing transmission risk. As snails are sensitive to environmental conditions, we expect their distribution is significantly impacted by global change. Here, we leveraged machine learning, remote sensing, and 30 years of snail occurrence records to map the historical and current distribution of competent Biomphalaria throughout Brazil. We identified key features influencing the distribution of suitable habitat and determined how Biomphalaria habitat has changed with climate and urbanization over the last three decades. Our models show that climate change has driven broad shifts in snail host range, whereas expansion of urban and peri-urban areas has driven localized increases in habitat suitability. Elucidating change in Biomphalaria distribution - while accounting for non-linearities that are difficult to detect from local case studies - can help inform schistosomiasis control strategies.

Minority-group incubators and majority-group reservoirs support the diffusion of climate change adaptations.

Successful climate change adaptation depends on the spread and maintenance of adaptive behaviours. Current theory suggests that the heterogeneity of metapopulation structure can help adaptations diffuse throughout a population. In this paper, we develop an agent-based model of the spread of adaptations in populations with minority-majority metapopulation structure, where subpopulations learn more or less frequently from their own group compared to the other group. In our simulations, minority-majority-structured populations with moderate degrees of in-group preference better spread and maintained an adaptation compared to populations with more equal-sized groups and weak homophily. Minority groups act as incubators for an adaptation, while majority groups act as reservoirs for an adaptation once it has spread widely. This means that adaptations diffuse throughout populations better when minority groups start out knowing an adaptation, as Indigenous populations often do, while cohesion among majority groups further promotes adaptation diffusion. Our work advances the goal of this theme issue by developing new theoretical insights and demonstrating the utility of cultural evolutionary theory and methods as important tools in the nascent science of culture that climate change adaptation needs. This article is part of the theme issue 'Climate change adaptation needs a science of culture'.

Survey of incidence, lifetime prevalence, and treatment of self-reported vulvovaginal candidiasis, United States, 2020.

BACKGROUND: Vulvovaginal candidiasis (VVC) is a common gynecologic problem in the United States but estimates of its true incidence and prevalence are lacking. We estimated self-reported incidence and lifetime prevalence of healthcare provider-diagnosed VVC and recurrent VVC (RVVC), assessed treatment types, and evaluated demographic and health-related risk factors associated with VVC. METHODS: An online survey sent to 4548 U.S. adults; data were weighted to be representative of the population. We conducted descriptive and bivariate analyses to examine demographic characteristics and health related factors associated with having VVC in the past year, lifetime prevalence of VVC, and over-the-counter (OTC) and prescription antifungal treatment use. We conducted multivariate analyses to assess features associated with 1) having VVC in the past year, 2) number of VVC episodes in the past year, and 3) lifetime prevalence of VVC. RESULTS: Among the subset of 1869 women respondents, 98 (5.2%) had VVC in the past year; of those, 5 (4.7%) had RVVC. Total, 991 (53%) women reported healthcare provider-diagnosed VVC in their lifetime. Overall, 72% of women with VVC in the past year reported prescription antifungal treatment use, 40% reported OTC antifungal treatment use, and 16% reported both. In multivariate analyses, odds of having VVC in the past year were highest for women with less than a high school education (aOR = 6.30, CI: 1.84-21.65), with a child/children under 18 years old (aOR = 3.14, CI: 1.58-6.25), with diabetes (aOR = 2.93, CI: 1.32-6.47), who were part of a couple (aOR = 2.86, CI: 1.42-5.78), and with more visits to a healthcare provider for any reason (aOR = 2.72, CI: 1.84-4.01). Similar factors were associated with increasing number of VVC episodes in the past year and with lifetime prevalence of VVC. CONCLUSION: VVC remains a common infection in the United States. Our analysis supports known clinical risk factors for VVC and suggests that antifungal treatment use is high, underscoring the need to ensure appropriate diagnosis and treatment.

Network structure and rapid HIV transmission among people who inject drugs: A simulation-based analysis.

As HIV incidence among people who inject drugs grows in the context of an escalating drug overdose epidemic in North America, investigating how network structure may affect vulnerability to rapid HIV transmission is necessary for preventing outbreaks. We compared the characteristics of the observed contact tracing network from the 2015 outbreak in rural Indiana with 1000 networks generated by an agent-based network model with approximately the same number of individuals (n = 420) and ties between them (n = 913). We introduced an initial HIV infection into the simulated networks and compared the subsequent epidemic behavior (e.g., cumulative HIV infections over 5 years). The model was able to produce networks with largely comparable characteristics and total numbers of incident HIV infections. Although the model was unable to produce networks with comparable cohesiveness (where the observed network had a transitivity value 35.7 standard deviations from the mean of the simulated networks), the structural variability of the simulated networks allowed for investigation into their potential facilitation of HIV transmission. These findings emphasize the need for continued development of injection network simulation studies in tandem with empirical data collection to further investigate how network characteristics played a role in this and future outbreaks.

Added Benefits of Pre-Exposure Prophylaxis Use on HIV Incidence with Minimal Changes in Efficiency in the Context of High Treatment Engagement Among Men Who Have Sex with Men.

Although there is ongoing debate over the need for substantial increases in pre-exposure prophylaxis (PrEP) use when antiretroviral treatment confers the dual benefits of reducing HIV-related morbidity and mortality and the risk of HIV transmission, no studies to date have quantified the potential added benefits of PrEP use and changes in its efficiency in the context of high treatment engagement across multiple US subpopulations. We used a previously published agent-based model to simulate HIV transmission in a dynamic network of Black/African American and White men who have sex with men (MSM) in Atlanta, Georgia (2015-2024) to understand how reductions in HIV incidence attributable to varying levels of PrEP use change when United Nations Joint Programme on HIV/AIDS (UNAIDS) "90-90-90" goals for HIV treatment are achieved and maintained. Even at achievement of "90-90-90" goals, 75% PrEP coverage further reduced incidence by 67.9% and 74.2% to 1.53 [simulation interval (SI): 1.39-1.70] and 0.355 (SI: 0.316-0.391) per 100 person-years for Black/African American and White MSM, respectively, compared with the same scenario with no PrEP use. Increasing PrEP coverage from 15% to 75% under "90-90-90" goals only increased the number of person-years of PrEP use per infection averted by 8.1% and 10.5% to 26.7 (SI: 25.6-28.0) and 73.3 (SI: 70.6-75.7) among Black/African American MSM and White MSM, respectively. Even with high treatment engagement, substantial expansion of PrEP use contributes to meaningful decreases in HIV incidence among MSM with minimal changes in efficiency.