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.

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.

Comparing the behavioural impact of a nudge-based handwashing intervention to high-intensity hygiene education: a cluster-randomised trial in rural Bangladesh.

OBJECTIVE: To determine the impact of environmental nudges on handwashing behaviours among primary school children as compared to a high-intensity hygiene education intervention. METHODS: In a cluster-randomised trial (CRT), we compared the rates of handwashing with soap (HWWS) after a toileting event among primary school students in rural Bangladesh. Eligible schools (government run, on-site sanitation and water, no hygiene interventions in last year, fewer than 450 students) were identified, and 20 schools were randomly selected and allocated without blinding to one of four interventions, five schools per group: simultaneous handwashing infrastructure and nudge construction, sequential infrastructure then nudge construction, simultaneous infrastructure and high-intensity hygiene education (HE) and sequential handwashing infrastructure and HE. The primary outcome, incidence of HWWS after a toileting event, was compared between the intervention groups at different data collection points with robust-Poisson regression analysis with generalised estimating equations, adjusting for school-level clustering of outcomes. RESULTS: The nudge intervention and the HE intervention were found to be equally effective at sustained impact over 5 months post-intervention (adjusted IRR 0.81, 95% CI 0.61-1.09). When comparing intervention delivery timing, the simultaneous delivery of the HE intervention significantly outperformed the sequential HE delivery (adjusted IRR 1.58 CI 1.20-2.08), whereas no significant difference was observed between sequential and simultaneous nudge intervention delivery (adjusted IRR 0.75, 95% CI 0.48-1.17). CONCLUSION: Our trial demonstrates sustained improved handwashing behaviour 5 months after the nudge intervention. The nudge intervention's comparable performance to a high-intensity hygiene education intervention is encouraging.

Social cohesion, social participation and HIV testing among men who have sex with men in Swaziland.

Social cohesion and social participation are social factors that may help reduce HIV risks and optimize health-seeking behaviors. We examined the association between these factors and HIV testing in the last 12 months among men who have sex with men (MSM) in Swaziland using a cross-sectional survey conducted with 326 men, 18 years of age or older reporting having sex with another man in the last 12 months. Social capital analyses included measures of social cohesion and social participation. The social cohesion measurement scale was created through exploratory factor analysis using polychoric correlations to determine unidimensionality and Cronbach's Alpha to assess internal consistency. The measurement scale was divided at the 25th and 75th percentiles using "high," "medium" and "low" levels of social cohesion for between-group comparisons. The social participation index included four questions regarding participation, resulting in a participation index ranging from 0 to 4. In the final multivariate logistic regression model, an increase in the level of social participation was found to be significantly associated with HIV testing in the last 12 months, adjusting for age, income, reporting a casual partner, family exclusion and rejection by other MSM due to sexual orientation (adjusted odds ratio [aOR]: 1.3, 95% confidence interval [CI] 1.1-1.7, p < .01). MSM with high social cohesion had almost twice the odds of HIV testing in the last 12 months (aOR: 1.8, 95% CI 1.1-3.3, p < .05) as MSM with medium social cohesion, though the overall social cohesion variable was not found to be significant using a Wald test in either the adjusted or unadjusted logistic regression models. These data suggest that building solidarity and trust within and between groups may be a strategy to improve uptake of HIV testing.

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.

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.

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 (NDWI) 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, investing in training geographic information systems professionals to leverage open-source environmental data could 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.

Predictors of bovine Schistosoma japonicum infection in rural Sichuan, China.

In China, bovines are believed to be the most common animal source of human schistosomiasis infections, though little is known about what factors promote bovine infections. The current body of literature features inconsistent, and sometimes contradictory results, and to date, few studies have looked beyond physical characteristics to identify the broader environmental conditions that predict bovine schistosomiasis. Because schistosomiasis is a sanitation-related, water-borne disease transmitted by many animals, we hypothesised that several environmental factors - such as the lack of improved sanitation systems, or participation in agricultural production that is water-intensive - could promote schistosomiasis infection in bovines. Using data collected as part of a repeat cross-sectional study conducted in rural villages in Sichuan, China from 2007 to 2016, we used a Random Forests, machine learning approach to identify the best physical and environmental predictors of bovine Schistosoma japonicum infection. Candidate predictors included: (i) physical/biological characteristics of bovines, (ii) human sources of environmental schistosomes, (iii) socio-economic indicators, (iv) animal reservoirs, and (v) agricultural practices. The density of bovines in a village and agricultural practices such as the area of rice and dry summer crops planted, and the use of night soil as an agricultural fertilizer, were among the top predictors of bovine S. japonicum infection in all collection years. Additionally, human infection prevalence, pig ownership and bovine age were found to be strong predictors of bovine infection in at least 1 year. Our findings highlight that presumptively treating bovines in villages with high bovine density or human infection prevalence may help to interrupt transmission. Furthermore, village-level predictors were stronger predictors of bovine infection than household-level predictors, suggesting future investigations may need to apply a broad ecological lens to identify potential underlying sources of persistent transmission.

The Association Between Rainfall, Temperature, and Reported Drinking Water Source: A Multi-Country Analysis.

Climate change may alter access to safe drinking water, with important implications for health. We assessed the relationship between temperature and rainfall and utilization of basic drinking water (BDW) in The Gambia, Mozambique, Pakistan, and Kenya. The outcomes of interest were (a) whether the reported drinking water source used in the past 2 weeks met the World Health Organization definition of BDW and (b) use of a BDW source that was always available. Temperature and precipitation data were compiled from weather stations and satellite data and summarized to account for long- and short-term weather patterns and lags. We utilized random forests and logistic regression to identify key weather variables that predicted outcomes by site and the association between important weather variables and BDW use. Higher temperatures were associated with decreased BDW use at three of four sites and decreased use of BDW that is always available at all four sites. Increasing rainfall, both in the long- and short-term, was associated with increased BDW use in three sites. We found evidence for interactions between household wealth and weather variables at two sites, suggesting lower wealth populations may be more sensitive to weather-driven changes in water access. Changes in temperature and precipitation can alter safe water use in low-resource settings-investigating drivers for these relationships can inform efforts to build climate resilience.

Social Influence on Handwashing with Soap: Results from a Cluster Randomized Controlled Trial in Bangladesh.

We analyzed data from a cluster-randomized controlled trial conducted among 20 schools in Rajshahi, Bangladesh, to explore the role of social influence on handwashing with soap (HWWS) in a primary school setting. Using data collected through covert video cameras outside of school latrines, we used robust Poisson regression analysis to assess the impact of social influence-defined as the presence of another person near the handwashing location-on HWWS after a toileting event. In adjusted analyses, we found a 30% increase in HWWS when someone was present, as compared with when a child was alone (Prevalence ratio 1.30; 95% confidence interval: 1.14-1.47, P < 0.001). The highest prevalence of HWWS was found when both child(ren) and adult(s) were present or when just children were present (64%). Our study supports the conclusion that the presence of another individual after a toileting event can positively impact HWWS in a primary school setting.

An exploration of emergency nurses' perceptions, attitudes and experience of teamwork in the emergency department.

BACKGROUND: Teamwork may assist with increased levels of efficiency and safety of patient care in the emergency department (ED), with emergency nurses playing an indispensable role in this process. METHOD: A descriptive, exploratory approach was used, drawing on principles from phenomenology and symbolic interactionism. Convenience, purposive sampling was used in a major metropolitan ED. Semi structured interviews were conducted, audio recorded, and transcribed verbatim. Transcripts were analysed using thematic analysis. RESULTS: Three major themes emerged from the data. The first theme 'when teamwork works' supported the notion that emergency nurses perceived teamwork as a positive and effective construct in four key areas; resuscitation, simulation training, patient outcomes and staff satisfaction. The second theme 'team support' revealed that back up behaviour and leadership were critical elements of team effectiveness within the study setting. The third theme 'no time for teamwork' centred around periods when teamwork practices failed due to various contributing factors including inadequate resources and skill mix. DISCUSSION: Outcomes of effective teamwork were valued by emergency nurses. Teamwork is about performance, and requires a certain skill set not necessarily naturally possessed among emergency nurses. Building a resilient team inclusive of strong leadership and communication skills is essential to being able to withstand the challenging demands of the ED.

An urgent need for integration of family planning services into HIV care: the high burden of unplanned pregnancy, termination of pregnancy, and limited contraception use among female sex workers in Côte d'Ivoire.

BACKGROUND: HIV infection and unintended pregnancy are occupational risks of commercial female sex work (FSW). The burden of unintended pregnancy among FSW including maternal and infant outcomes in the context of HIV is largely unknown. METHODS: FSW ≥18 years were recruited through respondent driven sampling into a cross-sectional study in Abidjan, Côte d'Ivoire. Participants completed a sociobehavioral questionnaire and HIV counseling and testing. Pregnancy history by HIV status and contraceptive use were described, and Poisson regression used to estimate correlates of termination of pregnancy (TOP). RESULTS: From March to July 2014, 466 FSW were enrolled. Unintended pregnancy was common, and 64% of participants had ≥1 TOP. Half of FSW experiencing TOPs did so without a medical professional, resulting in frequent complications. Contraceptive use was lowest among younger FSW, and 37% of 20-24 year olds reported multiple TOPs. FSW with a TOP history reported 19% less consistent condom use with clients than women who never had a TOP (adjusted-prevalence ratio, 0.81; 95% confidence interval: 0.74 to 0.88), whereas use of reliable nonbarrier contraceptive methods was comparable between the groups. Although FSW were engaged in HIV testing and prevention services, only 59% of FSW had received HIV testing before childbirth during their last pregnancy, and 30% of HIV-infected FSW had lost ≥1 children. CONCLUSIONS: Low contraceptive use and high burden of unintended pregnancy result in poor reproductive outcomes for FSW and avoidable mother-to-child HIV transmission risks. Integration of family planning and antenatal services into HIV prevention and care programs accessed by FSW could enhance reproductive outcomes and HIV prevention goals.