Open-source environmental data as an alternative to snail surveys to assess schistosomiasis risk in areas approaching elimination.

BACKGROUND: Although the presence of intermediate snails is a necessary condition for local schistosomiasis transmission to occur, using them as surveillance targets in areas approaching elimination is challenging because the patchy and dynamic quality of snail host habitats makes collecting and testing snails labor-intensive. Meanwhile, geospatial analyses that rely on remotely sensed data are becoming popular tools for identifying environmental conditions that contribute to pathogen emergence and persistence. METHODS: In this study, we assessed whether open-source environmental data can be used to predict the presence of human Schistosoma japonicum infections among households with a similar or improved degree of accuracy compared to prediction models developed using data from comprehensive snail surveys. To do this, we used infection data collected from rural communities in Southwestern China in 2016 to develop and compare the predictive performance of two Random Forest machine learning models: one built using snail survey data, and one using open-source environmental data. RESULTS: The environmental data models outperformed the snail data models in predicting household S. japonicum infection with an estimated accuracy and Cohen's kappa value of 0.89 and 0.49, respectively, in the environmental model, compared to an accuracy and kappa of 0.86 and 0.37 for the snail model. The Normalized Difference in Water Index (an indicator of surface water presence) within half to one kilometer of the home and the distance from the home to the nearest road were among the top performing predictors in our final model. Homes were more likely to have infected residents if they were further from roads, or nearer to waterways. CONCLUSION: Our results suggest that in low-transmission environments, leveraging open-source environmental data can yield more accurate identification of pockets of human infection than using snail surveys. Furthermore, the variable importance measures from our models point to aspects of the local environment that may indicate increased risk of schistosomiasis. For example, households were more likely to have infected residents if they were further from roads or were surrounded by more surface water, highlighting areas to target in future surveillance and control efforts.

Environmental Factors Influencing COVID-19 Incidence and Severity.

Emerging evidence supports a link between environmental factors-including air pollution and chemical exposures, climate, and the built environment-and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and coronavirus disease 2019 (COVID-19) susceptibility and severity. Climate, air pollution, and the built environment have long been recognized to influence viral respiratory infections, and studies have established similar associations with COVID-19 outcomes. More limited evidence links chemical exposures to COVID-19. Environmental factors were found to influence COVID-19 through four major interlinking mechanisms: increased risk of preexisting conditions associated with disease severity; immune system impairment; viral survival and transport; and behaviors that increase viral exposure. Both data and methodologic issues complicate the investigation of these relationships, including reliance on coarse COVID-19 surveillance data; gaps in mechanistic studies; and the predominance of ecological designs. We evaluate the strength of evidence for environment-COVID-19 relationships and discuss environmental actions that might simultaneously address the COVID-19 pandemic, environmental determinants of health, and health disparities.

Estimating the Impact of Statewide Policies to Reduce Spread of Severe Acute Respiratory Syndrome Coronavirus 2 in Real Time, Colorado, USA.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic necessitated rapid local public health response, but studies examining the impact of social distancing policies on SARS-CoV-2 transmission have struggled to capture regional-level dynamics. We developed a susceptible-exposed-infected-recovered transmission model, parameterized to Colorado, USA‒specific data, to estimate the impact of coronavirus disease‒related policy measures on mobility and SARS-CoV-2 transmission in real time. During March‒June 2020, we estimated unknown parameter values and generated scenario-based projections of future clinical care needs. Early coronavirus disease policy measures, including a stay-at-home order, were accompanied by substantial decreases in mobility and reduced the effective reproductive number well below 1. When some restrictions were eased in late April, mobility increased to near baseline levels, but transmission remained low (effective reproductive number <1) through early June. Over time, our model parameters were adjusted to more closely reflect reality in Colorado, leading to modest changes in estimates of intervention effects and more conservative long-term projections.

Viral CpG Deficiency Provides No Evidence That Dogs Were Intermediate Hosts for SARS-CoV-2.

Due to the scope and impact of the COVID-19 pandemic there exists a strong desire to understand where the SARS-CoV-2 virus came from and how it jumped species boundaries to humans. Molecular evolutionary analyses can trace viral origins by establishing relatedness and divergence times of viruses and identifying past selective pressures. However, we must uphold rigorous standards of inference and interpretation on this topic because of the ramifications of being wrong. Here, we dispute the conclusions of Xia (2020. Extreme genomic CpG deficiency in SARS-CoV-2 and evasion of host antiviral defense. Mol Biol Evol. doi:10.1093/molbev/masa095) that dogs are a likely intermediate host of a SARS-CoV-2 ancestor. We highlight major flaws in Xia's inference process and his analysis of CpG deficiencies, and conclude that there is no direct evidence for the role of dogs as intermediate hosts. Bats and pangolins currently have the greatest support as ancestral hosts of SARS-CoV-2, with the strong caveat that sampling of wildlife species for coronaviruses has been limited.

Human Mobility Associated With Risk of Schistosoma japonicum Infection in Sichuan, China.

Urbanization increases human mobility in ways that can alter the transmission of classically rural, vector-borne diseases like schistosomiasis. The impact of human mobility on individual-level Schistosoma risk is poorly characterized. Travel outside endemic areas may protect against infection by reducing exposure opportunities, whereas travel to other endemic regions may increase risk. Using detailed monthly travel- and water-contact surveys from 27 rural communities in Sichuan, China, in 2008, we aimed to describe human mobility and to identify mobility-related predictors of S. japonicum infection. Candidate predictors included timing, frequency, distance, duration, and purpose of recent travel as well as water-contact measures. Random forests machine learning was used to detect key predictors of individual infection status. Logistic regression was used to assess the strength and direction of associations. Key mobility-related predictors include frequent travel and travel during July-both associated with decreased probability of infection and less time engaged in risky water-contact behavior, suggesting travel may remove opportunities for schistosome exposure. The importance of July travel and July water contact suggests a high-risk window for cercarial exposure. The frequency and timing of human movement out of endemic areas should be considered when assessing potential drivers of rural infectious diseases.

Spatiotemporal Error in Rainfall Data: Consequences for Epidemiologic Analysis of Waterborne Diseases.

The relationship between rainfall, especially extreme rainfall, and increases in waterborne infectious diseases is widely reported in the literature. Most of this research, however, has not formally considered the impact of exposure measurement error contributed by the limited spatiotemporal fidelity of precipitation data. Here, we evaluate bias in effect estimates associated with exposure misclassification due to precipitation data fidelity, using extreme rainfall as an example. We accomplished this via a simulation study, followed by analysis of extreme rainfall and incident diarrheal disease in an epidemiologic study in Ecuador. We found that the limited fidelity typical of spatiotemporal rainfall data sets biases effect estimates towards the null. Use of spatial interpolations of rain-gauge data or satellite data biased estimated health effects due to extreme rainfall (occurrence) and wet conditions (accumulated totals) downwards by 35%-45%. Similar biases were evident in the Ecuadorian case study analysis, where spatial incompatibility between exposed populations and rain gauges resulted in the association between extreme rainfall and diarrheal disease incidence being approximately halved. These findings suggest that investigators should pay greater attention to limitations in using spatially heterogeneous environmental data sets to assign exposures in epidemiologic research.

Relationships between home ventilation rates and respiratory health in the Colorado Home Energy Efficiency and Respiratory Health (CHEER) study.

BACKGROUND: As societies adopt green building practices to reduce energy expenditures and emissions that contribute to climate change, it is important to consider how such building design changes influence health. These practices typically focus on reducing air exchange rates between the building interior and the outdoor environment to minimize energy loss, the health effects of which are not well characterized. This study aims to evaluate the relationship between air exchange rates and respiratory health in a multi-ethnic population living in low-income, urban homes. METHODS: The Colorado Home Energy Efficiency and Respiratory Health (CHEER) study is a cross-sectional study that enrolled 302 people in 216 non-smoking, low-income single-family homes, duplexes and town-homes from Colorado's Northern Front Range. A blower door test was conducted and the annual average air exchange rate (AAER) was estimated for each home. Respiratory health was assessed using a structured questionnaire based on standard instruments. We estimated the association between AAER and respiratory symptoms, adjusting for relevant confounders. RESULTS: Air exchange rates in many homes were high compared to prior studies (median 0.54 air changes per hour, range 0.10, 2.17). Residents in homes with higher AAER were more likely to report chronic cough, asthma and asthma-like symptoms, including taking medication for wheeze, wheeze that limited activities and dry cough at night. Allergic symptoms were not associated with AAER in any models. The association between AAER and asthma-like symptoms was stronger for households located in areas with high potential exposure to traffic related pollutants, but this was not consistent across all health outcomes. CONCLUSIONS: While prior studies have highlighted the potential hazards of low ventilation rates in residences, this study suggests high ventilation rates in single-family homes, duplexes and town-homes in urban areas may also have negative impacts on respiratory health, possibly due to the infiltration of outdoor pollutants.

Evaluation of heat stress and cumulative incidence of acute kidney injury in sugarcane workers in Guatemala.

OBJECTIVE: Agricultural workers worldwide exposed to heat stress could be at the risk of kidney injury, which could lead to chronic kidney disease of an unknown origin (CKDu). Hydration has been promoted as a key measure to reduce kidney injury. In the presence of a hydration intervention, the incidence of acute kidney injury (AKI) was calculated in a sugarcane worker population in Guatemala and several risk factors were evaluated. METHODS: We measured kidney function at the beginning and end of the work shift at three time points in 517 sugarcane workers. We defined AKI as an increase in serum creatinine of 26.5 µmol/L or 50% or more from the pre-shift value. Associations between AKI and risk factors were examined, including interactions with hydration status. RESULTS: The prevalence of dehydration post-shift (> 1.020 specific gravity) was 11% in February, 9% in March, and 6% in April. Cumulative incidence of AKI was 53% in February, 54% in March, and 51% in April. AKI was associated with increasing post-shift specific gravity, a dehydration marker, (OR 1.24, 95% CI 1.02-1.52) and with lower electrolyte solution intake (OR 0.94, 95% CI 0.89-0.99). CONCLUSIONS: Dehydration and insufficient electrolyte consumption are risk factors for AKI. However even well-hydrated sugarcane workers routinely experience AKI. While hydration is important and protective, there is a need to understand other contributors to risk of AKI and identify prevention strategies with these workers.

Preliminary genetic evidence of two different populations of Opisthorchis viverrini in Lao PDR.

Opisthorchis viverrini is a major public health concern in Southeast Asia. Various reports have suggested that this parasite may represent a species complex, with genetic structure in the region perhaps being dictated by geographical factors and different species of intermediate hosts. We used four microsatellite loci to analyze O. viverrini adult worms originating from six species of cyprinid fish in Thailand and Lao PDR. Two distinct O. viverrini populations were observed. In Ban Phai, Thailand, only one subgroup occurred, hosted by two different fish species. Both subgroups occurred in fish from That Luang, Lao PDR, but were represented to very different degrees among the fish hosts there. Our data suggest that, although geographical separation is more important than fish host specificity in influencing genetic structure, it is possible that two species of Opisthorchis, with little interbreeding, are present near Vientiane in Lao PDR.

Untangling the Impacts of Climate Change on Waterborne Diseases: a Systematic Review of Relationships between Diarrheal Diseases and Temperature, Rainfall, Flooding, and Drought.

Global climate change is expected to affect waterborne enteric diseases, yet to date there has been no comprehensive, systematic review of the epidemiological literature examining the relationship between meteorological conditions and diarrheal diseases. We searched PubMed, Embase, Web of Science, and the Cochrane Collection for studies describing the relationship between diarrheal diseases and four meteorological conditions that are expected to increase with climate change: ambient temperature, heavy rainfall, drought, and flooding. We synthesized key areas of agreement and evaluated the biological plausibility of these findings, drawing from a diverse, multidisciplinary evidence base. We identified 141 articles that met our inclusion criteria. Key areas of agreement include a positive association between ambient temperature and diarrheal diseases, with the exception of viral diarrhea and an increase in diarrheal disease following heavy rainfall and flooding events. Insufficient evidence was available to evaluate the effects of drought on diarrhea. There is evidence to support the biological plausibility of these associations, but publication bias is an ongoing concern. Future research evaluating whether interventions, such as improved water and sanitation access, modify risk would further our understanding of the potential impacts of climate change on diarrheal diseases and aid in the prioritization of adaptation measures.

Heavy rainfall events and diarrhea incidence: the role of social and environmental factors.

The impact of heavy rainfall events on waterborne diarrheal diseases is uncertain. We conducted weekly, active surveillance for diarrhea in 19 villages in Ecuador from February 2004 to April 2007 in order to evaluate whether biophysical and social factors modify vulnerability to heavy rainfall events. A heavy rainfall event was defined as 24-hour rainfall exceeding the 90th percentile value (56 mm) in a given 7-day period within the study period. Mixed-effects Poisson regression was used to test the hypothesis that rainfall in the prior 8 weeks, water and sanitation conditions, and social cohesion modified the relationship between heavy rainfall events and diarrhea incidence. Heavy rainfall events were associated with increased diarrhea incidence following dry periods (incidence rate ratio = 1.39, 95% confidence interval: 1.03, 1.87) and decreased diarrhea incidence following wet periods (incidence rate ratio = 0.74, 95% confidence interval: 0.59, 0.92). Drinking water treatment reduced the deleterious impacts of heavy rainfall events following dry periods. Sanitation, hygiene, and social cohesion did not modify the relationship between heavy rainfall events and diarrhea. Heavy rainfall events appear to affect diarrhea incidence through contamination of drinking water, and they present the greatest health risks following periods of low rainfall. Interventions designed to increase drinking water treatment may reduce climate vulnerability.

Surveillance systems for neglected tropical diseases: global lessons from China's evolving schistosomiasis reporting systems, 1949-2014.

Though it has been a focus of the country's public health surveillance systems since the 1950s, schistosomiasis represents an ongoing public health challenge in China. Parallel, schistosomiasis-specific surveillance systems have been essential to China's decades-long campaign to reduce the prevalence of the disease, and have contributed to the successful elimination in five of China's twelve historically endemic provinces, and to the achievement of morbidity and transmission control in the other seven. More recently, an ambitious goal of achieving nation-wide transmission interruption by 2020 has been proposed. This paper details how schistosomiasis surveillance systems have been structured and restructured within China's evolving public health system, and how parallel surveillance activities have provided an information system that has been integral to the characterization of, response to, and control of the disease. With the ongoing threat of re-emergence of schistosomiasis in areas previously considered to have achieved transmission control, a critical examination of China's current surveillance capabilities is needed to direct future investments in health information systems and to enable improved coordination between systems in support of ongoing control. Lessons drawn from China's experience are applied to the current global movement to reduce the burden of helminthiases, where surveillance capacity based on improved diagnostics is urgently needed.

Does behavior mediate the effect of weather on SARS-CoV-2 transmission? evidence from cell-phone data.

There is growing evidence that weather alters SARS-CoV-2 transmission, but it remains unclear what drives the phenomenon. One prevailing hypothesis is that people spend more time indoors in cooler weather, leading to increased spread of SARS-CoV-2 related to time spent in confined spaces and close contact with others. However, the evidence in support of that hypothesis is limited and, at times, conflicting. We use a mediation framework, and combine daily weather, COVID-19 hospital surveillance, cellphone-based mobility data and building footprints to estimate the relationship between daily indoor and outdoor weather conditions, mobility, and COVID-19 hospitalizations. We quantify the direct health impacts of weather on COVID-19 hospitalizations and the indirect effects of weather via time spent indoors away-from-home on COVID-19 hospitalizations within five Colorado counties between March 4th 2020 and January 31st 2021. We also evaluated the evidence for seasonal effect modification by comparing the results of all-season (using season as a covariate) to season-stratified models. Four weather conditions were associated with both time spent indoors away-from-home and 12-day lagged COVID-19 hospital admissions in one or more season: high minimum temperature (all-season), low maximum temperature (spring), low minimum absolute humidity (winter), and high solar radiation (all-season & winter). In our mediation analyses, we found evidence that changes in 12-day lagged hospital admissions were primarily via the direct effects of weather conditions, rather than via indirect effects by which weather changes time spent indoors away-from-home. Our findings do not support the hypothesis that weather impacted SARS-CoV-2 transmission via changes in mobility patterns during the first year of the pandemic. Rather, weather appears to have impacted SARS-CoV-2 transmission primarily via mechanisms other than human movement. We recommend further analysis of this phenomenon to determine whether these findings generalize to current SARS-CoV-2 transmission dynamics, as well as other seasonal respiratory pathogens.

Did COVID-19 ICU patient mortality risk increase as Colorado hospitals filled? A retrospective cohort study.

OBJECTIVES: To assess whether increasing levels of hospital stress-measured by intensive care unit (ICU) bed occupancy (primary), ventilators in use and emergency department (ED) overflow-were associated with decreasing COVID-19 ICU patient survival in Colorado ICUs during the pre-Delta, Delta and Omicron variant eras. DESIGN: A retrospective cohort study using discrete-time survival models, fit with generalised estimating equations. SETTING: 34 hospital systems in Colorado, USA, with the highest patient volume ICUs during the COVID-19 pandemic. PARTICIPANTS: 9196 non-paediatric SARS-CoV-2 patients in Colorado hospitals admitted once to an ICU between 1 August 2020 and 1 March 2022 and followed for 28 days. OUTCOME MEASURES: Death or discharge to hospice. RESULTS: For Delta-era COVID-19 ICU patients in Colorado, the odds of death were estimated to be 26% greater for patients exposed every day of their ICU admission to a facility experiencing its all-era 75th percentile ICU fullness or above, versus patients exposed for none of their days (OR: 1.26; 95% CI: 1.04 to 1.54; p=0.0102), adjusting for age, sex, length of ICU stay, vaccination status and hospital quality rating. For both Delta-era and Omicron-era patients, we also detected significantly increased mortality hazard associated with high ventilator utilisation rates and (in a subset of facilities) states of ED overflow. For pre-Delta-era patients, we estimated relatively null or even protective effects for the same fullness exposures, something which provides a meaningful contrast to previous studies that found increased hazards but were limited to pre-Delta study windows. CONCLUSIONS: Overall, and especially during the Delta era (when most Colorado facilities were at their fullest), increasing exposure to a fuller hospital was associated with an increasing mortality hazard for COVID-19 ICU patients.

Does behavior mediate the effect of weather on SARS-CoV-2 transmission? Evidence from cell-phone data.

Background: There is growing evidence that weather alters SARS-CoV-2 transmission, but it remains unclear what drives the phenomenon. One prevailing hypothesis is that people spend more time indoors in cooler weather, leading to increased spread of SARS-CoV-2 related to time spent in confined spaces and close contact with others. However, the evidence in support of that hypothesis is limited and, at times, conflicting. Objectives: We aim to evaluate the extent to which weather impacts COVID-19 via time spent away-from-home in indoor spaces, as compared to a direct effect of weather on COVID-19 hospitalization, independent of mobility. Methods: We use a mediation framework, and combine daily weather, COVID-19 hospital surveillance, cellphone-based mobility data and building footprints to estimate the relationship between daily indoor and outdoor weather conditions, mobility, and COVID-19 hospitalizations. We quantify the direct health impacts of weather on COVID-19 hospitalizations and the indirect effects of weather via time spent indoors away-from-home on COVID-19 hospitalizations within five Colorado counties between March 4th 2020 and January 31st 2021. Results: We found evidence that changes in 12-day lagged hospital admissions were primarily via the direct effects of weather conditions, rather than via indirect effects by which weather changes time spent indoors away-from-home. Sensitivity analyses evaluating time at home as a mediator were consistent with these conclusions. Discussion: Our findings do not support the hypothesis that weather impacted SARS-CoV-2 transmission via changes in mobility patterns during the first year of the pandemic. Rather, weather appears to have impacted SARS-CoV-2 transmission primarily via mechanisms other than human movement. We recommend further analysis of this phenomenon to determine whether these findings generalize to current SARS-CoV-2 transmission dynamics and other seasonal respiratory pathogens.

Investigating the relationship between extreme weather and cryptosporidiosis and giardiasis in Colorado: A multi-decade study using distributed-lag nonlinear models.

Environmentally-mediated protozoan diseases like cryptosporidiosis and giardiasis are likely to be highly impacted by extreme weather, as climate-related conditions like temperature and precipitation have been linked to their survival, distribution, and overall transmission success. Our aim was to investigate the relationship between extreme temperature and precipitation and cryptosporidiosis and giardiasis infection using monthly weather data and case reports from Colorado counties over a twenty-one year period. Data on reportable diseases and weather among Colorado counties were collected using the Colorado Electronic Disease Reporting System (CEDRS) and the Daily Surface Weather and Climatological Summaries (Daymet) Version 3 dataset, respectively. We used a conditional Poisson distributed-lag nonlinear modeling approach to estimate the lagged association (between 0 and 12-months) between relative temperature and precipitation extremes and the risk of cryptosporidiosis and giardiasis infection in Colorado counties between 1997 and 2017, relative to the risk found at average values of temperature and precipitation for a given county and month. We found distinctly different patterns in the associations between temperature extremes and cryptosporidiosis, versus temperature extremes and giardiasis. When maximum or minimum temperatures were high (90th percentile) or very high (95th percentile), we found a significant increase in cryptosporidiosis risk, but a significant decrease in giardiasis risk, relative to risk at the county and calendar-month mean. Conversely, we found very similar relationships between precipitation extremes and both cryptosporidiosis and giardiasis, which highlighted the prominent role of long-term (>8 months) lags. Our study presents novel insights on the influence that extreme temperature and precipitation can have on parasitic disease transmission in real-world settings. Additionally, we present preliminary evidence that the standard lag periods that are typically used in epidemiological studies to assess the impacts of extreme weather on cryptosporidiosis and giardiasis may not be capturing the entire relevant period.

Urbanisation and health in China.

China has seen the largest human migration in history, and the country's rapid urbanisation has important consequences for public health. A provincial analysis of its urbanisation trends shows shifting and accelerating rural-to-urban migration across the country and accompanying rapid increases in city size and population. The growing disease burden in urban areas attributable to nutrition and lifestyle choices is a major public health challenge, as are troubling disparities in health-care access, vaccination coverage, and accidents and injuries in China's rural-to-urban migrant population. Urban environmental quality, including air and water pollution, contributes to disease both in urban and in rural areas, and traffic-related accidents pose a major public health threat as the country becomes increasingly motorised. To address the health challenges and maximise the benefits that accompany this rapid urbanisation, innovative health policies focused on the needs of migrants and research that could close knowledge gaps on urban population exposures are needed.

Approaches to genotyping individual miracidia of Schistosoma japonicum.

Molecular genetic tools are needed to address questions as to the source and dynamics of transmission of the human blood fluke Schistosoma japonicum in regions where human infections have reemerged, and to characterize infrapopulations in individual hosts. The life stage that interests us as a target for collecting genotypic data is the miracidium, a very small larval stage that consequently yields very little DNA for analysis. Here, we report the successful development of a multiplex format permitting genotyping of 17 microsatellite loci in four sequential multiplex reactions using a single miracidium held on a Whatman Classic FTA indicating card. This approach was successful after short storage periods, but after long storage (>4 years), considerable difficulty was encountered in multiplex genotyping, necessitating the use of whole genome amplification (WGA) methods. WGA applied to cards stored for long periods of time resulted in sufficient DNA for accurate and repeatable genotyping. Trials and tests of these methods, as well as application to some field-collected samples, are reported, along with the discussion of the potential insights to be gained from such techniques. These include recognition of sibships among miracidia from a single host, and inference of the minimum number of worm pairs that might be present in a host.

Regional disparities in the burden of disease attributable to unsafe water and poor sanitation in China.

OBJECTIVE: To estimate the disease burden attributable to unsafe water and poor sanitation and hygiene in China, to identify high-burden groups and to inform improvement measures. METHODS: The disease burden attributable to unsafe water and poor sanitation and hygiene in China was estimated for diseases resulting from exposure to biologically contaminated soil and water (diarrhoeal disease, helminthiases and schistosomiasis) and vector transmission resulting from inadequate management of water resources (malaria, dengue and Japanese encephalitis). The data were obtained from China's national infectious disease reporting system, national helminthiasis surveys and national water and sanitation surveys. The fraction of each health condition attributable to unsafe water and poor sanitation and hygiene in China was estimated from data in the Chinese and international literature. FINDINGS: In 2008, 327 million people in China lacked access to piped drinking water and 535 million lacked access to improved sanitation. The same year, unsafe water and poor sanitation and hygiene accounted for 2.81 million disability-adjusted life years (DALYs) and 62,800 deaths in the country, and 83% of the attributable burden was found in children less than 5 years old. Per capita DALYs increased along an east-west gradient, with the highest burden in inland provinces having the lowest income per capita. CONCLUSION: Despite remarkable progress, China still needs to conduct infrastructural improvement projects targeting provinces that have experienced slower economic development. Improved monitoring, increased regulatory oversight and more government transparency are needed to better estimate the effects of microbiologically and chemically contaminated water and poor sanitation and hygiene on human health.

A genomic can of worms for schistosome host-specificity.

Understanding the genetic underpinnings of schistosome host preferences is critical. Luo et al. recently identified genes associated with intermediate and definitive host-switching based on a new chromosome-level genome for Schistosoma japonicum, population genetic comparisons, and follow-up experiments. This represents a guide to fully map-selected schistosome genes using population genetics.