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Optimal control theory can be a useful tool to identify the best strategies for the management of infectious diseases. In most of the applications to disease control with ordinary differential equations, the objective functional to be optimized is formulated in monetary terms as the sum of intervention costs and the cost associated with the burden of disease. We present alternate formulations that express epidemiological outcomes via health metrics and reframe the problem to include features such as budget constraints and epidemiological targets. These alternate formulations are illustrated with a compartmental cholera model. The alternate formulations permit us to better explore the sensitivity of the optimal control solutions to changes in available budget or the desired epidemiological target. We also discuss some limitations of comprehensive cost assessment in epidemiology.

BackgroundDrought is an understudied driver of infectious disease dynamics. Amidst the ongoing southwestern North American megadrought, California (USA) is having the driest multi-decadal period since 800 CE, exacerbated by anthropogenic warming. In this study, we aimed to examine the influence of drought on coccidioidomycosis, an emerging infectious disease in southwestern USA.MethodsWe analysed California census tract-level surveillance data from 2000 to 2020 using generalised additive models and distributed monthly lags on precipitation and temperature. We then developed an ensemble prediction algorithm of incident cases of coccidioidomycosis per census tract to estimate the counterfactual incidence that would have occurred in the absence of drought.FindingsBetween April 1, 2000, and March 31, 2020, there were 81 448 reported cases of coccidioidomycosis throughout California. An estimated 1467 excess cases of coccidioidomycosis were observed in California in the 2 years following the drought that occurred between 2007 and 2009, and an excess 2649 drought-attributable cases of coccidioidomycosis were observed in the 2 years following the drought that occurred between 2012 and 2015. These increased numbers of cases more than offset the declines in cases that occurred during drought. An IQR increase in summer temperatures was associated with 2·02 (95% CI 1·84-2·22) times higher incidence in the following autumn (September to November), and an IQR increase in precipitation in the winter was associated with 1·45 (1·36-1·55) times higher incidence in the autumn. The effect of winter precipitation was 36% (25-48) stronger when preceded by two dry, rather than average, winters. Incidence in arid counties was most sensitive to precipitation fluctuations, while incidence in wetter counties was most sensitive to temperature.InterpretationIn California, multi-year cycles of dry conditions followed by a wet winter increases transmission of coccidioidomycosis, especially in historically wetter areas. With anticipated increasing frequency of drought in southwestern USA, continued expansion of coccidioidomycosis, along with more intense seasons, is expected. Our results motivate the need for heightened precautions against coccidioidomycosis in seasons that follow major droughts.FundingNational Institutes of Health.

With the aid of laboratory typing techniques, infectious disease surveillance networks have the opportunity to obtain powerful information on the emergence, circulation, and evolution of multiple genotypes, serotypes or other subtypes of pathogens, informing understanding of transmission dynamics and strategies for prevention and control. The volume of typing performed on clinical isolates is typically limited by its ability to inform clinical care, cost and logistical constraints, especially in comparison with the capacity to monitor clinical reports of disease occurrence, which remains the most widespread form of public health surveillance. Viewing clinical disease reports as arising from a latent mixture of pathogen subtypes, laboratory typing of a subset of clinical cases can provide inference on the proportion of clinical cases attributable to each subtype (i.e., the mixture components). Optimizing protocols for the selection of isolates for typing by weighting specific subpopulations, locations, time periods, or case characteristics (e.g., disease severity), may improve inference of the frequency and distribution of pathogen subtypes within and between populations. Here, we apply the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework to simulate and optimize hand foot and mouth disease (HFMD) surveillance in a high-burden region of western China. We identify laboratory surveillance designs that significantly outperform the existing network: the optimal network reduced mean absolute error in estimated serotype-specific incidence rates by 14.1%; similarly, the optimal network for monitoring severe cases reduced mean absolute error in serotype-specific incidence rates by 13.3%. In both cases, the optimal network designs achieved improved inference without increasing subtyping effort. We demonstrate how the DIOS framework can be used to optimize surveillance networks by augmenting clinical diagnostic data with limited laboratory typing resources, while adapting to specific, local surveillance objectives and constraints.

Global health and development communities lack sustainable, cost-effective, mutually beneficial solutions for infectious disease, food, water, and poverty challenges despite their regular interdependence worldwide1–7. Here, we show that agricultural development and fertilizer use in west Africa increase the devastating tropical disease schistosomiasis by fueling the growth of submerged aquatic vegetation that chokes out water access points and serves as habitat for snails that transmit Schistosoma parasites to >200 million people globally8–10. In a randomized control trial where we removed invasive submerged vegetation from water points, control sites had 124% higher fecal Schistosoma reinfection rates in schoolchildren and lower open water access than removal sites without any detectable long-term adverse effects of the removal on local water quality or freshwater biodiversity. The removed vegetation was as effective as traditional livestock feed but 41-179 times cheaper and converting the vegetation to compost yielded private crop production and total (public health plus private benefits) benefit-to-cost ratios as high as 4.0 and 8.8, respectively. Thus, we provide an economic incentive – with important public health co-benefits – to maintain cleared waterways and return nutrients captured in aquatic plants back to agriculture with great promise of breaking poverty-disease traps. To facilitate targeting and scaling of this intervention, we lay the foundation for using remote sensing technology to detect snail habitat. By offering a rare, profitable, win-win innovation for food and water access, poverty, infectious disease emergence, and environmental sustainability, we hope to inspire the interdisciplinary search for other planetary health solutions11 to the numerous and formidable, co-dependent global grand challenges of the 21st century.

We review the interaction between coronavirus disease (COVID-19) and coccidioidomycosis, a respiratory infection caused by inhalation of Coccidioides fungal spores in dust. We examine risk for co-infection among construction and agricultural workers, incarcerated persons, Black and Latino populations, and persons living in high dust areas. We further identify common risk factors for co-infection, including older age, diabetes, immunosuppression, racial or ethnic minority status, and smoking. Because these diseases cause similar symptoms, the COVID-19 pandemic might exacerbate delays in coccidioidomycosis diagnosis, potentially interfering with prompt administration of antifungal therapies. Finally, we examine the clinical implications of co-infection, including severe COVID-19 and reactivation of latent coccidioidomycosis. Physicians should consider coccidioidomycosis as a possible diagnosis when treating patients with respiratory symptoms. Preventive measures such as wearing face masks might mitigate exposure to dust and severe acute respiratory syndrome coronavirus 2, thereby protecting against both infections.

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.

Passive surveillance systems are widely used to monitor diseases occurrence over wide spatial areas due to their cost-effectiveness and integration into broadly distributed healthcare systems. However, such systems are generally associated with imperfect ascertainment of disease cases and with heterogeneous capture probabilities arising from factors such as differential access to care. Augmenting passive surveillance systems with other surveillance efforts provides a way to estimate the true number of incident cases. We develop a hierarchical modeling framework for analyzing data from multiple surveillance systems that allows for individual-level covariate-dependent heterogeneous capture probabilities, and borrows information across surveillance sites to improve estimation of the true number of incident cases. Inference is carried out via a two-stage Bayesian procedure. Simulation studies illustrated superior performance of the proposed approach with respect to bias, root mean square error, and coverage compared to a model that does not borrow information across sites. We applied the proposed model to data from three surveillance systems reporting pulmonary tuberculosis (PTB) cases in a major center of ongoing transmission in China. The analysis yielded bias-corrected estimates of PTB cases from the passive system and led to the identification of risk factors associated with PTB rates, as well as factors influencing the operating characteristics of the implemented surveillance systems.

Summary Background Agrochemical pollution of surface waters is a growing global environmental challenge, especially in areas where agriculture is rapidly expanding and intensifying. Agrochemicals might affect schistosomiasis transmission through direct and indirect effects on Schistosoma parasites, their intermediate snail hosts, snail predators, and snail algal resources. We aimed to review and summarise the effects of these agrochemicals on schistosomiasis transmission dynamics. Methods We did a systematic review of agrochemical effects on the lifecycle of Schistosoma spp and fitted dose-response models to data regarding the association between components of the lifecycle and agrochemical concentrations. We incorporated these dose-response functions and environmentally relevant concentrations of agrochemicals into a mathematical model to estimate agrochemical effects on schistosomiasis transmission. Dose-response functions were used to estimate individual agrochemical effects on estimates of the agrochemically influenced basic reproduction number, R0, for Schistosoma haematobium. We incorporated time series of environmentally relevant agrochemical concentrations into the model and simulated mass drug administration control efforts in the presence of agrochemicals. Findings We derived 120 dose-response functions describing the effects of agrochemicals on schistosome lifecycle components. The median estimate of the basic reproduction number under agrochemical-free conditions, was 1·65 (IQR 1·47–1·79). Agrochemical effects on estimates of R0 for S haematobium ranged from a median three-times increase (R0 5·05, IQR 4·06–5·97) to transmission elimination (R0 0). Simulations of transmission dynamics subject to interacting annual mass drug administration and agrochemical pollution yielded a median estimate of 64·82 disability-adjusted life-years (DALYs) lost per 100 000 people per year (IQR 62·52–67·68) attributable to atrazine use. In areas where aquatic arthropod predators of intermediate host snails suppress transmission, the insecticides chlorpyrifos (6·82 DALYs lost per 100 000 people per year, IQR 4·13–8·69) and profenofos (103·06 DALYs lost per 100 000 people per year, IQR 89·63–104·90) might also increase the disability burden through their toxic effects on arthropods. Interpretation Expected environmental concentrations of agrochemicals alter schistosomiasis transmission through direct and indirect effects on intermediate host and parasite densities. As industrial agricultural practices expand in areas where schistosomiasis is endemic, strategies to prevent increases in transmission due to agrochemical pollution should be developed and pursued. Funding National Science Foundation, National Institutes of Health.

BackgroundCoccidioidomycosis is an emerging infection in the southwestern United States. We examined the effects of precipitation and temperature on the incidence of coccidioidomycosis in California during 2000-2020, and estimated incident cases attributable to the California droughts of 2007-09 and 2012-15.MethodsWe analyzed monthly California coccidioidomycosis surveillance data from 2000–2020 at the census tract-level using generalized additive models. Models included distributed lags of precipitation and temperature within each endemic county, pooled using fixed-effects meta-analysis. An ensemble prediction algorithm of incident cases per census tract was developed to estimate the impact of drought on expected cases.ResultsAcross 14 counties examined, coccidioidomycosis was strongly suppressed during, and amplified following, the 2007-2009 and 2012-2015 droughts. An estimated excess of 1,358 and 2,461 drought-attributable cases were observed in California in the two years following the 2007-2009 and 2012-2015 droughts, respectively. These post-drought excess cases more than offset the drought-attributable declines of 1,126 and 2,192 cases, respectively, that occurred during the 2007-2009 and 2012-2015 droughts. Across counties, a temperature increase from the 25th to 75th percentile (interquartile range) in the summer was associated with a doubling of incidence in the following fall (incidence rate ratio (IRR): 2.02, 95% CI: 1.84, 2.22), and a one IQR increase in precipitation in the winter was associated with 1.45 (95% CI: 1.36, 1.55) times higher incidence in the fall. The effect of winter precipitation was stronger (interaction coefficient representing ratio of IRRs: 1.36, 95% CI: 1.25, 1.48) when preceded by two dry rather than average winters. Incidence in arid lower San Joaquin Valley counties was most sensitive to winter precipitation fluctuations, while incidence in wetter coastal counties was most sensitive to summer temperature fluctuations.ConclusionsIn California, wet winters along with hot summers, particularly those following previous dry years, increased risk of coccidioidomycosis in California. Drought conditions may suppress incidence, then amplify incidence in subsequent years. With anticipated increasing frequency of drought in California, continued expansion of incidence, particularly in wetter, coastal regions, is expected.

Use of agrochemicals, including insecticides, is vital to food production and predicted to increase 2-5 fold by 2050. Previous studies have shown a positive association between agriculture and the human infectious disease schistosomiasis, which is problematic as this parasitic disease infects approximately 250 million people worldwide. Certain insecticides might runoff fields and be highly toxic to invertebrates, such as prawns in the genus Macrobrachium, that are biocontrol agents for snails that transmit the parasites causing schistosomiasis. We used a laboratory dose-response experiment and an observational field study to determine the relative toxicities of three pyrethroid (esfenvalerate, λ-cyhalothrin, and permethrin) and three organophosphate (chlorpyrifos, malathion, and terbufos) insecticides to Macrobrachium prawns. In the lab, pyrethroids were consistently several orders of magnitude more toxic than organophosphate insecticides, and more likely to runoff fields at lethal levels according to modeling data. At 31 water contact sites in the lower basin of the Senegal River where schistosomiasis is endemic, we found that Macrobrachium prawn survival was associated with pyrethroid but not organophosphate application rates to nearby crop fields after controlling for abiotic and prawn-level factors. Our laboratory and field results suggest that widely used pyrethroid insecticides can have strong non-target effects on Macrobrachium prawns that are biocontrol agents where 400 million people are at risk of human schistosomiasis. Understanding the ecotoxicology of high-risk insecticides may help improve human health in schistosomiasis-endemic regions undergoing agricultural expansion.

Background Reliable and field-applicable diagnosis of schistosome infections in non-human animals is important for surveillance, control, and verification of interruption of human schistosomiasis transmission. This study aimed to summarize uses of available diagnostic techniques through a systematic review and meta-analysis. Methodology and principal findings We systematically searched the literature and reports comparing two or more diagnostic tests in non-human animals for schistosome infection. Out of 4,909 articles and reports screened, 19 met our inclusion criteria, four of which were considered in the meta-analysis. A total of 14 techniques (parasitologic, immunologic, and molecular) and nine types of non-human animals were involved in the studies. Notably, four studies compared parasitologic tests (miracidium hatching test (MHT), Kato-Katz (KK), the Danish Bilharziasis Laboratory technique (DBL), and formalin-ethyl acetate sedimentation-digestion (FEA-SD)) with quantitative polymerase chain reaction (qPCR), and sensitivity estimates (using qPCR as the reference) were extracted and included in the meta-analyses, showing significant heterogeneity across studies and animal hosts. The pooled estimate of sensitivity was 0.21 (95% confidence interval (CI): 0.03–0.48) with FEA-SD showing highest sensitivity (0.89, 95% CI: 0.65–1.00). Conclusions/significance Our findings suggest that the parasitologic technique FEA-SD and the molecular technique qPCR are the most promising techniques for schistosome diagnosis in non-human animal hosts. Future studies are needed for validation and standardization of the techniques for real-world field applications.

Schistosome parasites infect more than 200 million people annually, mostly in sub-Saharan Africa, where people may be co-infected with more than one species of the parasite. Infection risk for any single species is determined, in part, by the distribution of its obligate intermediate host snail. As the World Health Organization reprioritizes snail control to reduce the global burden of schistosomiasis, there is renewed importance in knowing when and where to target those efforts, which could vary by schistosome species. This study estimates factors associated with schistosomiasis risk in 16 villages located in the Senegal River Basin, a region hyperendemic for Schistosoma haematobium and S. mansoni. We first analyzed the spatial distributions of the two schistosomes’ intermediate host snails (Bulinus spp. and Biomphalaria pfeifferi, respectively) at village water access sites. Then, we separately evaluated the relationships between human S. haematobium and S. mansoni infections and (i) the area of remotely-sensed snail habitat across spatial extents ranging from 1 to 120 m from shorelines, and (ii) water access site size and shape characteristics. We compared the influence of snail habitat across spatial extents because, while snail sampling is traditionally done near shorelines, we hypothesized that snails further from shore also contribute to infection risk. We found that, controlling for demographic variables, human risk for S. haematobium infection was positively correlated with snail habitat when snail habitat was measured over a much greater radius from shore (45 m to 120 m) than usual. S. haematobium risk was also associated with large, open water access sites. However, S. mansoni infection risk was associated with small, sheltered water access sites, and was not positively correlated with snail habitat at any spatial sampling radius. Our findings highlight the need to consider different ecological and environmental factors driving the transmission of each schistosome species in co-endemic landscapes., Author summary Schistosome parasites infect more than 200 million people worldwide, mainly in sub-Saharan Africa, where many people are at-risk for infection by multiple schistosome species simultaneously. To reduce the global burden of schistosomiasis, control of the parasites’ intermediate host–specific species of freshwater snails–has been elevated in priority to complement mass drug administration campaigns in endemic areas. To maximize the efficacy and efficiency of snail control efforts, a better understanding of where to target intermediate host snails is badly needed. This includes a better understanding of the spatial scale at which snails in the environment contribute to human infection risk, and, in co-endemic settings, how ecological determinants of infection risk vary by schistosome species. We used quantitative snail sampling and remotely-sensed data at 16 villages in the Senegal River Basin to compare and contrast ecological correlates and spatial scales of infection risk from freshwater snails that transmit Schistosoma haematobium versus S. mansoni. We found that infection risk for S. haematobium was associated with snail habitat at a larger spatial radius than is typically considered for schistosomiasis monitoring and control, whereas infection risk for S. mansoni was not positively correlated with snail habitat at any spatial sampling radius, but was associated with small water access sites enclosed by emergent vegetation. Our findings highlight the need to consider the different ecological and environmental factors driving the transmission of each schistosome species in co-endemic landscapes.

Background The San Francisco Bay Area was the first region in the United States to enact school closures to mitigate SARS-CoV-2 transmission. The effects of closures on contact patterns for schoolchildren and their household members remain poorly understood. Methods We conducted serial cross-sectional surveys (May 2020, September 2020, February 2021) of Bay Area households with children to estimate age-structured daily contact rates for children and their adult household members. We examined changes in contact rates over the course of the COVID-19 pandemic, including after vaccination of household members, and compared contact patterns by household demographics using generalized estimating equations clustered by household. Results We captured contact histories for 1,967 households on behalf of 2,674 children, comprising 15,087 non-household contacts over the three waves of data collection. Shortly after the start of shelter-in-place orders in May 2020, daily contact rates were higher among children from Hispanic families (1.52 more contacts per child per day; [95% CI: 1.14–2.04]), households whose parents were unable to work from home (1.82; [1.40–2.40]), and households with income Conclusions Child contact rates rebounded despite schools remaining closed, as parents obtained childcare, children engaged in contact in non-school settings, and family members were vaccinated. The waning reductions observed in non-household contact rates of schoolchildren and their family members during a prolonged school closure suggests the strategy may be ineffective for long-term SARS-CoV-2 transmission mitigation. Reductions in age-assortative contacts were not as apparent amongst children from lower income households or households where adults could not work from home. Heterogeneous reductions in contact patterns raise concerning racial, ethnic and income-based inequities associated with long-term school closures as a COVID-19 mitigation strategy.

Background China contributed 8.9% of all incident cases of tuberculosis globally in 2017, and understanding the spatiotemporal distribution of pulmonary tuberculosis (PTB) in major transmission foci in the country is critical to ongoing efforts to improve population health. Methods We estimated annual PTB notification rates and their spatiotemporal distributions in Sichuan province, a major center of ongoing transmission, from 2005 to 2017. Time series decomposition was used to obtain trend components from the monthly incidence rate time series. Spatiotemporal cluster analyses were conducted to detect spatiotemporal clusters of PTB at the county level. Results From 2005 to 2017, 976,873 cases of active PTB and 388,739 cases of smear-positive PTB were reported in Sichuan Province, China. During this period, the overall reported incidence rate of active PTB decreased steadily at a rate of decrease (3.77 cases per 100,000 per year, 95% confidence interval (CI): 3.28–4.31) that was slightly faster than the national average rate of decrease (3.14 cases per 100,000 per year, 95% CI: 2.61–3.67). Although reported PTB incidence decreased significantly in most regions of the province, incidence was observed to be increasing in some counties with high HIV incidence and ethnic minority populations. Active and smear-positive PTB case reports exhibited seasonality, peaking in March and April, with apparent links to social dynamics and climatological factors. Conclusions While PTB incidence rates decreased strikingly in the study area over the past decade, improvements have not been equally distributed. Additional surveillance and control efforts should be guided by the seasonal-trend and spatiotemporal cluster analyses presented here, focusing on areas with increasing incidence rates, and updated to reflect the latest information from real-time reporting. Electronic supplementary material The online version of this article (10.1186/s12879-019-4262-2) contains supplementary material, which is available to authorized users.

Infectious diseases are emerging globally at an unprecedented rate while global food demand is projected to increase sharply by 2100. Here, we synthesize the pathways by which projected agricultural expansion and intensification will influence human infectious diseases and how human infectious diseases might likewise affect food production and distribution. Feeding 11 billion people will require substantial increases in crop and animal production that will expand agricultural use of antibiotics, water, pesticides and fertilizer, and contact rates between humans and both wild and domestic animals, all with consequences for the emergence and spread of infectious agents. Indeed, our synthesis of the literature suggests that, since 1940, agricultural drivers were associated with >25% of all — and >50% of zoonotic — infectious diseases that emerged in humans, proportions that will likely increase as agriculture expands and intensifies. We identify agricultural and disease management and policy actions, and additional research, needed to address the public health challenge posed by feeding 11 billion people., Population growth and economic development affect and are affected by infectious diseases and food production. This Review synthesizes understanding about the links between emerging infectious diseases and food production, finding strong associations worldwide.

Mass gatherings exacerbate infectious disease risks by creating crowded, high-contact conditions and straining the capacity of local infrastructure. While mass gatherings have been extensively studied in the context of epidemic disease transmission, the role of gatherings in incidence of high-burden, endemic infections has not been previously studied. Here, we examine diarrheal incidence among 17 communities in Esmeraldas, Ecuador, in relation to recurrent gatherings characterized using ethnographic data collected during and after the epidemiologic surveillance period (2004–2007). Using distributed-lag generalized estimating equations, adjusted for seasonality, trend, and heavy rainfall events, we found significant increases in diarrhea risk in host villages, peaking 2 weeks after an event’s conclusion (incidence rate ratio, 1.21; confidence interval, adjusted for false coverage rate of ≤0.05: 1.02, 1.43). Stratified analysis revealed heightened risks associated with events where crowding and travel were most likely (2-week-lag incidence rate ratio, 1.51; confidence interval, adjusted for false coverage rate of ≤0.05: 1.09, 2.10). Our findings suggest that community-scale mass gatherings might play an important role in endemic diarrheal disease transmission and could be an important focus for interventions to improve community health in low-resource settings.

The signs of climate change are undeniable, and the inevitable impact for Earth and all its inhabitants is a serious concern. Ice is melting, sea levels are rising, biodiversity is declining, precipitation has increased, atmospheric levels of carbon dioxide and greenhouse gases are alarmingly high, and extreme weather conditions are becoming increasingly common. But what role do microorganisms have in this global challenge? In this Viewpoint article, several experts in the field discuss the microbial contributions to climate change and consider the effects of global warming, extreme weather, flooding and other consequences of climate change on microbial communities in the ocean and soil, on host-microbiota interactions and on the global burden of infectious diseases and ecosystem processes, and they explore open questions and research needs.

Background Reliable and field-applicable diagnosis of schistosome infections in non-human animals is important for surveillance, control, and verification of interruption of human schistosomiasis transmission. This study aimed to summarize uses of available diagnostic techniques through a systematic review and meta-analysis. Methods and principal findings We systematically searched the literature and reports comparing two or more diagnostic tests in non-human animals for schistosome infection. Out of 4,909 articles and reports screened, 18 met our inclusion criteria, four of which were considered in the meta-analysis. A total of 14 techniques (parasitologic, immunologic, and molecular) and nine types of non-human animals were involved in the studies. Notably, four studies compared parasitologic tests (miracidium hatching test (MHT), Kato-Katz (KK), the Danish Bilharziasis Laboratory technique (DBL), and formalin-ethyl acetate sedimentation-digestion (FED-SD)) with quantitative polymerase chain reaction (qPCR), and sensitivity estimates (using qPCR as the reference) were extracted and included in the meta-analyses, showing significant heterogeneity across studies and animals hosts. The pooled estimate of sensitivity was 0.21 (95% confidence interval (CI): 0.03 – 0.48) with FED-SD showing highest sensitivity (0.89, 95% CI: 0.65 – 1.00). Conclusions and significance Our findings suggest that the parasitologic technique FEA-SD and the molecular technique, qPCR, are the most promising field-applicable techniques for schistosome diagnosis in non-human animal hosts. Future studies are needed for validation and standardization of the techniques for real-world field applications.

International audience; As sustainable development practitioners have worked to "ensure healthy lives and promote well-being for all" and "conserve life on land and below water", what progress has been made with win-win interventions that reduce human infectious disease burdens while advancing conservation goals? Using a systematic literature review, we identified 46 proposed solutions, which we then investigated individually using targeted literature reviews. The proposed solutions addressed diverse conservation threats and human infectious diseases, and thus, the proposed interventions varied in scale, costs, and impacts. Some potential solutions had medium-quality to high-quality evidence for previous success in achieving proposed impacts in one or both sectors. However, there were notable evidence gaps within and among solutions, highlighting opportunities for further research and adaptive implementation. Stakeholders seeking win-win interventions can explore this Review and an online database to find and tailor a relevant solution or brainstorm new solutions.

We thank Li et al. (1) for their interest in our paper (2) and agree that different approaches to estimating famine intensity, expressed here as the cohort size shrinkage index (CSSI), could affect estimates of its association with tuberculosis (TB) risk in the birth cohort directly impacted by famine. We acknowledge their contention that our published CSSI estimates could be biased upward due to postfamine increases in fertility that suggest delayed births. However, the proposal to use only prefamine (1953 to 1957) births to estimate the counterfactual size of the famine cohort (1958 to 1962) strikes us as ill-advised, since it ignores secular increases in cohort size that are clearly observable in data for Sichuan Province (Fig. 1) and for China as a whole (3). We respond here by examining alternative approaches to estimating the counterfactual cohort size and their impacts on estimates of the … [↵][1]1To whom correspondence may be addressed. Email: jvr{at}berkeley.edu. [1]: #xref-corresp-1-1

Background Large-scale school closures have been implemented worldwide to curb the spread of COVID-19. However, the impact of school closures and re-opening on epidemic dynamics remains unclear. Methods We simulated COVID-19 transmission dynamics using an individual-based stochastic model, incorporating social-contact data of school-aged children during shelter-in-place orders derived from Bay Area (California) household surveys. We simulated transmission under observed conditions and counterfactual intervention scenarios between March 17-June 1, and evaluated various fall 2020 K-12 reopening strategies. Findings Between March 17-June 1, assuming children

Synthetic chemicals, such as pesticides, have increased faster than other agents of global change have, yet their ecological impacts remain understudied. Additionally, agricultural expansion to address human population growth and food shortages is predicted to increase the use of pesticides, some of which have been linked to increases in infectious diseases of humans, such as schistosomiasis, which infects >250 million people worldwide. Previous work revealed that ecologically relevant concentrations of organophosphate and pyrethroid insecticides are highly toxic to crayfish. Whether these same insecticides are also highly toxic to Macrobrachium rosenbergii and M. vollenhovenii prawns, which are closely related to crayfish and are important predators on snails that transmit schistosomiasis in Asia and Africa, respectively, is unknown. We performed laboratory dose-response studies for M. rosenbergii using three pyrethroid (esfenvalerate, λ-cyhalothrin, and permethrin) and three organophosphate (chlorpyrifos, malathion, and terbufos) insecticides. Pyrethroid LC50 values were consistently several orders of magnitude lower than for organophosphate insecticides. Pyrethroids also had a greater likelihood of field runoff at levels lethal to prawns. To corroborate these findings in natural settings, we experimentally tracked survival of individually caged M. vollenhovenii at 31 waterways in West Africa that varied widely in their insecticide use. Consistent with laboratory results, pyrethroid insecticide use in these villages was positively associated with Macrobrachium mortality when controlling for village-level and prawn-level attributes, including levels of organophosphate applications. Villages with the most pyrethroid use had lower prawn survival, despite using on average 20% less total insecticides than villages with high prawn survival. Our findings suggest that pyrethroid insecticides widely used in sub-Saharan Africa have strong non-target effects on Macrobrachium spp. prawns, with possible implications for human schistosomiasis. Thus, regulations or incentives to avoid high-risk insecticides, especially near waterways, could have important human health implications in countries undergoing agricultural expansion in schistosomiasis-endemic regions.

The California state government put restrictions on outdoor residential water use, including landscape irrigation, during the 2012-2016 drought. The public health implications of these actions are largely unknown, particularly with respect to mosquito-borne disease transmission. While residential irrigation facilitates persistence of mosquitoes by increasing the availability of standing water, few studies have investigated its effects on vector abundance. In two study sub-regions in the Los Angeles Basin, we examined the effect of outdoor residential water use restrictions on the abundance of the most important regional West Nile virus vector, Culex quinquefasciatus. Using spatiotemporal random forest models fit to Cx. abundance during drought and non-drought years, we generated counterfactual estimates of Cx. abundance under a hypothetical drought scenario without water use restrictions. We estimate that Cx. abundance would have been 44% and 39% larger in West Los Angeles and Orange counties, respectively, if outdoor water usage had remained unchanged. Our results suggest that drought, without mandatory water use restrictions, may counterintuitively increase the availability of larval habitats for vectors in naturally dry, highly irrigated settings and such mandatory water use restrictions may constrain Cx. abundance, which could reduce the risk of mosquito-borne disease while helping urban utilities maintain adequate water supplies.

Infectious disease surveillance systems provide vital data for guiding disease prevention and control policies, yet the formalization of methods to optimize surveillance networks has largely been overlooked. Decisions surrounding surveillance design parameters—such as the number and placement of surveillance sites, target populations, and case definitions—are often determined by expert opinion or deference to operational considerations, without formal analysis of the influence of design parameters on surveillance objectives. Here we propose a simulation framework to guide evidence-based surveillance network design to better achieve specific surveillance goals with limited resources. We define evidence-based surveillance design as an optimization problem, acknowledging the many operational constraints under which surveillance systems operate, the many dimensions of surveillance system design, the multiple and competing goals of surveillance, and the complex and dynamic nature of disease systems. We describe an analytical framework—the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework—for the identification of optimal surveillance designs through mathematical representations of disease and surveillance processes, definition of objective functions, and numerical optimization. We then apply the framework to the problem of selecting candidate sites to expand an existing surveillance network under alternative objectives of: (1) improving spatial prediction of disease prevalence at unmonitored sites; or (2) estimating the observed effect of a risk factor on disease. Results of this demonstration illustrate how optimal designs are sensitive to both surveillance goals and the underlying spatial pattern of the target disease. The findings affirm the value of designing surveillance systems through quantitative and adaptive analysis of network characteristics and performance. The framework can be applied to the design of surveillance systems tailored to setting-specific disease transmission dynamics and surveillance needs, and can yield improved understanding of tradeoffs between network architectures., Author summary Disease surveillance systems are essential for understanding the epidemiology of infectious diseases and improving population health. A well-designed surveillance system can achieve a high level of fidelity in estimates of interest (e.g., disease trends, risk factors) within its operational constraints. Currently, design parameters that define surveillance systems (e.g., number and placement of the surveillance sites, target populations, case definitions) are selected largely by expert opinion and practical considerations. Such an informal approach is less tenable when multiple aspects of surveillance design—or multiple surveillance objectives—need to be considered simultaneously, and are subject to resource or logistical constraints. Here we propose a framework to optimize surveillance system design given a set of defined surveillance objectives and a dynamical model of the disease system under study. The framework provides a platform for in silico surveillance system design, and allows the formulation of surveillance guidelines based on quantitative evidence, tailored to local realities and priorities. The framework is designed to facilitate greater collaboration between health planners and computational and data scientists to advance surveillance science and strengthen the architecture of surveillance networks.

Background Enterovirus 71 (EV71) is a major causative agent of hand, foot, and mouth disease (HFMD), associated with severe manifestations of the disease. Pediatric immunization with inactivated EV71 vaccine was initiated in 2016 in the Asia-Pacific region, including China. We analyzed a time series of HFMD cases attributable to EV71, coxsackievirus A16 (CA16), and other enteroviruses in Chengdu, a major transmission center in China, to assess early impacts of immunization. Methods Reported HFMD cases were obtained from China’s notifiable disease surveillance system. We compared observed postvaccination incidence rates during 2017–2018 with counterfactual predictions made from a negative binomial regression and a random forest model fitted to prevaccine years (2011–2015). We fit a change point model to the full time series to evaluate whether the trend of EV71 HFMD changed following vaccination. Results Between 2011 and 2018, 279 352 HFMD cases were reported in the study region. The average incidence rate of EV71 HFMD in 2017–2018 was 60% (95% prediction interval [PI], 41%–72%) lower than predicted in the absence of immunization, corresponding to an estimated 6911 (95% PI, 3246–11 542) EV71 cases averted over 2 years. There were 52% (95% PI, 42%–60%) fewer severe HFMD cases than predicted. However, the incidence rate of non-CA16 and non-EV71 HFMD was elevated in 2018. We identified a significant decline in the trend of EV71 HFMD 4 months into the postvaccine period. Conclusions We provide the first real-world evidence that programmatic vaccination against EV71 is effective against childhood HFMD and present an approach to detect early vaccine impact or intended consequences from surveillance data.

Disease surveillance data are important for monitoring disease burden and occurrence, and for informing a wide range of efforts to improve population health. Surveillance for infectious diseases may be conducted passively, relying on reports from healthcare facilities, or actively, involving surveys of the population at risk. Passive surveillance typically provides wide spatial coverage, but is subject to biases arising from differences in care-seeking behavior, diagnostic practices, and under-reporting. Active surveillance minimizes these biases, but is typically constrained to small areas and subpopulations due to resource limitations. Methods based on linkage of individual records between passive and active surveillance datasets provide a means to estimate and correct for the biases of each system, leveraging the size and coverage of passive surveillance and the quality of data in active surveillance. We develop a spatial Bayesian hierarchical model for bias-correcting data from both systems to yield an improved estimate of disease measures after adjusting for under-ascertainment. We apply the framework to data from a passive and an active surveillance system for pulmonary tuberculosis (PTB) in Sichuan, China, and estimate the average sensitivity of the active surveillance system at 70% (95% credible interval: 62%, 78%), and the passive system at 30% (95% CI: 24%, 35%). Passive surveillance sensitivity exhibited considerable spatial variability, and was positively associated with a site’s gross domestic product per capita. Bias-corrected estimates of county-level PTB prevalence in the province in 2010 identified regions in the southeast with the highest PTB burden, yielding different geographic priorities than previous reports.

Global food security is a major driver of population health, and food system collapse may have complex and long-lasting effects on health outcomes. We examined the effect of prenatal exposure to the Great Chinese Famine (1958-1962)-the largest famine in human history-on pulmonary tuberculosis (PTB) across consecutive generations in a major center of ongoing transmission in China. We analyzed >1 million PTB cases diagnosed between 2005 and 2018 in Sichuan Province using age-period-cohort analysis and mixed-effects metaregression to estimate the effect of the famine on PTB risk in the directly affected birth cohort (F1) and their likely offspring (F2). The analysis was repeated on certain sexually transmitted and blood-borne infections (STBBI) to explore potential mechanisms of the intergenerational effects. A substantial burden of active PTB in the exposed F1 cohort and their offspring was attributable to the Great Chinese Famine, with more than 12,000 famine-attributable active PTB cases (>1.23% of all cases reported between 2005 and 2018). An interquartile range increase in famine intensity resulted in a 6.53% (95% confidence interval [CI]: 1.19-12.14%) increase in the ratio of observed to expected incidence rate (incidence rate ratio, IRR) in the absence of famine in F1, and an 8.32% (95% CI: 0.59-16.6%) increase in F2 IRR. Increased risk of STBBI was also observed in F2. Prenatal and early-life exposure to malnutrition may increase the risk of active PTB in the exposed generation and their offspring, with the intergenerational effect potentially due to both within-household transmission and increases in host susceptibility.

Temperature is widely known to influence the spatio-temporal dynamics of vector-borne disease transmission, particularly as temperatures vary across critical thermal thresholds. When temperature conditions exhibit such ‘transcritical variation’, abrupt spatial or temporal discontinuities may result, generating sharp geographical or seasonal boundaries in transmission. Here, we develop a spatio-temporal machine learning algorithm to examine the implications of transcritical variation for West Nile virus (WNV) transmission in the Los Angeles metropolitan area (LA). Analysing a large vector and WNV surveillance dataset spanning 2006–2016, we found that mean temperatures in the previous month strongly predicted the probability of WNV presence in pools of Culex quinquefasciatus mosquitoes, forming distinctive inhibitory (10.0–21.0°C) and favourable (22.7–30.2°C) mean temperature ranges that bound a narrow 1.7°C transitional zone (21–22.7°C). Temperatures during the most intense months of WNV transmission (August/September) were more strongly associated with infection probability in Cx. quinquefasciatus pools in coastal LA, where temperature variation more frequently traversed the narrow transitional temperature range compared to warmer inland locations. This contributed to a pronounced expansion in the geographical distribution of human cases near the coast during warmer-than-average periods. Our findings suggest that transcritical variation may influence the sensitivity of transmission to climate warming, and that especially vulnerable locations may occur where present climatic fluctuations traverse critical temperature thresholds.

Recent evidence suggests that snail predators may aid efforts to control the human parasitic disease schistosomiasis by eating aquatic snail species that serve as intermediate hosts of the parasite. Here, potential synergies between schistosomiasis control and aquaculture of giant prawns are evaluated using an integrated bioeconomic–epidemiological model. Combinations of stocking density and aquaculture cycle length that maximize cumulative, discounted profit are identified for two prawn species in sub-Saharan Africa: the endemic, non-domesticated Macrobrachium vollenhovenii and the non-native, domesticated Macrobrachium rosenbergii. At profit-maximizing densities, both M. rosenbergii and M. vollenhovenii may substantially reduce intermediate host snail populations and aid schistosomiasis control efforts. Control strategies drawing on both prawn aquaculture to reduce intermediate host snail populations and mass drug administration to treat infected individuals are found to be superior to either strategy alone. Integrated aquaculture-based interventions can be a win–win strategy in terms of health and sustainable development in schistosomiasis endemic regions of the world. Predators, including prawns, can suppress schistosomiasis by eating snail hosts. This modelling study finds that two prawn species in sub-Saharan Africa can reduce snail hosts and help control schistosomiasis at densities that maximize profits of associated aquaculture—a potential win–win.

Infectious disease surveillance systems provide vital data for guiding disease prevention and control policies, yet the formalization of methods to optimize surveillance networks has largely been overlooked. Decisions surrounding surveillance design parameters—such as the number and placement of surveillance sites, target populations, and case definitions—are often determined by expert opinion or deference to operational considerations, without formal analysis of the influence of design parameters on surveillance objectives. Here we propose a simulation framework to guide evidence-based surveillance network design to better achieve specific surveillance goals with limited resources. We define evidence-based surveillance design as a constrained, multi-dimensional, multi-objective, dynamic optimization problem, acknowledging the many operational constraints under which surveillance systems operate, the many dimensions of surveillance system design, the multiple and competing goals of surveillance, and the complex and dynamic nature of disease systems. We describe an analytical framework for the identification of optimal designs through mathematical representations of disease and surveillance processes, definition of objective functions, and the approach to numerical optimization. We then apply the framework to the problem of selecting candidate sites to expand an existing surveillance network under alternative objectives of: (1) improving spatial prediction of disease prevalence at unmonitored sites; or (2) estimating the observed effect of a risk factor on disease. Results of this demonstration illustrate how optimal designs are sensitive to both surveillance goals and the underlying spatial pattern of the target disease. The findings affirm the value of designing surveillance systems through quantitative and adaptive analysis of network characteristics and performance. The framework can be applied to the design of surveillance systems tailored to setting-specific disease transmission dynamics and surveillance needs, and can yield improved understanding of tradeoffs between network architectures.Author summaryDisease surveillance systems are essential for understanding the epidemiology of infectious diseases and improving population health. A well-designed surveillance system can achieve a high level of fidelity in estimates of interest (e.g., disease trends, risk factors) within its operational constraints. Currently, design parameters that define surveillance systems (e.g., number and placement of the surveillance sites, target populations, case definitions) are selected largely by expert opinion and practical considerations. Such an informal approach is less tenable when multiple aspects of surveillance design—or multiple surveillance objectives— need to be considered simultaneously, and are subject to resource or logistical constraints. Here we propose a framework to optimize surveillance system design given a set of defined surveillance objectives and a dynamical model of the disease system under study. The framework provides a platform to conduct in silico surveillance system design, and allows the formulation of surveillance guidelines based on quantitative evidence, tailored to local realities and priorities. The approach facilitates greater collaboration between health planners and computational and data scientists to advance surveillance science and strengthen the architecture of surveillance networks.

Climate exerts complex influences on leptospirosis transmission, affecting human behavior, zoonotic host population dynamics, and survival of the pathogen in the environment. Here, we describe the spatiotemporal distribution of leptospirosis incidence reported to China’s National Infectious Disease Surveillance System from 2004–2014 in an endemic region in western China, and employ distributed lag models at annual and sub-annual scales to analyze its association with hydroclimatic risk factors and explore evidence for the potential role of a soil reservoir in the transmission of Leptospira spp. More than 97% of the 2,934 reported leptospirosis cases occurred during the harvest season between August and October, and most commonly affected farmers (83%). Using a distributed lag Poisson regression framework, we characterized incidence rate ratios (IRRs) associated with interquartile range increases in precipitation of 3.45 (95% confidence interval 2.57–4.64) over 0-1-year lags, and 1.90 (1.18–3.06) over 0-15-week lags. Adjusting for soil moisture decreased IRRs for precipitation at both timescales (yearly adjusted IRR: 1.05, 0.74–1.49; weekly adjusted IRR: 1.36, 0.72–2.57), suggesting precipitation effects may be mediated through soil moisture. Increased soil moisture was positively associated with leptospirosis at both timescales, suggesting that the survival of pathogenic Leptospira spp. in moist soils may be a critical control on harvest-associated leptospirosis transmission in the study region. These results support the hypothesis that soils may serve as an environmental reservoir and may play a significant yet underrecognized role in leptospirosis transmission., Author summary Leptospirosis is among the leading causes of morbidity from zoonotic infections worldwide, affecting populations that are exposed to contaminated water. The disease is caused by Leptospira spp. bacteria, which are transmitted to humans either through direct contact with infected animals, or indirectly through the environment. Climatic conditions can influence transmission by altering human exposure, animal host population dynamics, and environmental conditions that allow Leptospira spp. to persist in the environment (e.g., moist environments, warm temperatures). Here, we investigated the spatiotemporal distribution of leptospirosis cases in a rural setting in western China and estimated the association between hydroclimatic conditions and leptospirosis incidence. We found that incidence of leptospirosis—especially high amongst farmers—may be associated with rice harvest, and modulated by prior bacterial accumulation within the soil under moist conditions. These results corroborate previous findings that soils may be underrecognized environmental reservoirs of pathogenic Leptospira spp., and that their role in explaining leptospirosis incidence should be considered when developing prevention programs.

Summary Transportation-related risk factors are a major source of morbidity and mortality in China, where the expansion of road networks and surges in personal vehicle ownership are having profound effects on public health. Road traffic injuries and fatalities have increased alongside increased use of motorised transport in China, and accident injury risk is aggravated by inadequate emergency response systems and trauma care. National air quality standards and emission control technologies are having a positive effect on air quality, but persistent air pollution is increasingly attributable to a growing and outdated vehicle fleet and to famously congested roads. Urban design favours motorised transport, and physical activity and its associated health benefits are hindered by poor urban infrastructure. Transport emissions of greenhouse gases contribute substantially to regional and global climate change, which compound public health risks from multiple factors. Despite these complex challenges, technological advances and innovations in planning and policy stand to make China a leader in sustainable, healthy transportation.

Background Noroviruses are the leading cause of acute gastroenteritis and foodborne diarrheal disease in the United States. Norovirus vaccine development has progressed in recent years, but critical questions remain regarding which age groups should be vaccinated to maximize population impact. Methods We developed a deterministic, age-structured compartmental model of norovirus transmission and immunity in the U.S. population. The model was fit to age-specific monthly U.S. hospitalizations between 1996 and 2007. We simulated mass immunization of both pediatric and elderly populations assuming realistic coverages of 90% and 65%, respectively. We considered two mechanism of vaccine action, resulting in lower vaccine efficacy (lVE) between 22% and 43% and higher VE (hVE) of 50%. Results Pediatric vaccination was predicted to avert 33% (95% CI: 27%, 40%) and 60% (95% CI: 49%, 71%) of norovirus episodes among children under five years for lVE and hVE, respectively. Vaccinating the elderly averted 17% (95% CI: 12%, 20%) and 38% (95% CI: 34%, 42%) of cases in 65+ year olds for lVE and hVE, respectively. At a population level, pediatric vaccination was predicted to avert 18–21 times more cases and twice as many deaths per vaccinee compared to elderly vaccination. Conclusions The potential benefits are likely greater for a pediatric program, both via direct protection of vaccinated children and indirect protection of unvaccinated individuals, including adults and the elderly. These findings argue for a clinical development plan that will deliver a vaccine with a safety and efficacy profile suitable for use in children.

In the Anthropocene, in which we now live, climate change is impacting most life on Earth. Microorganisms support the existence of all higher trophic life forms. To understand how humans and other life forms on Earth (including those we are yet to discover) can withstand anthropogenic climate change, it is vital to incorporate knowledge of the microbial ‘unseen majority’. We must learn not just how microorganisms affect climate change (including production and consumption of greenhouse gases) but also how they will be affected by climate change and other human activities. This Consensus Statement documents the central role and global importance of microorganisms in climate change biology. It also puts humanity on notice that the impact of climate change will depend heavily on responses of microorganisms, which are essential for achieving an environmentally sustainable future., Nature Reviews Microbiology, 17 (9), ISSN:1740-1526, ISSN:1740-1534

Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies to investigate the long-term effects of environmental, behavioural, psycho-social, and biological factors on health-related states and events and the underlying mechanisms. With the growing number of studies reporting findings from this field and the critical need for public health and policy decisions to be based on the strongest science possible, transparency and clarity in reporting in spatial lifecourse epidemiologic studies is essential. A task force supported by the International Initiative on Spatial Lifecourse Epidemiology (ISLE) identified a need for guidance in this area and developed a Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) Statement. The aim is to provide a checklist of recommendations to improve and make more consistent reporting of spatial lifecourse epidemiologic studies. The STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement for cohort studies was identified as an appro-priate starting point to provide initial items to consider for inclusion. Reporting standards for spatial data and methods were then integrated to form a single comprehensive checklist of reporting recommendations. The strength of our approach has been our international and multidisciplinary team of content experts and con-tributors who represent a wide range of relevant scientific conventions, and our adherence to international norms for the development of reporting guidelines. As spatial, location-based, and artificial intelligence technologies used in spatial lifecourse epidemiology continue to evolve at a rapid pace, it will be necessary to revisit and adapt the ISLE-ReSt at least every 2-3 years from its release.

Background Schistosomiasis is responsible for the second highest burden of disease among neglected tropical diseases globally, with over 90 percent of cases occurring in African regions where drugs to treat the disease are only sporadically available. Additionally, human re-infection after treatment can be a problem where there are high numbers of infected snails in the environment. Recent experiments indicate that aquatic factors, including plants, nutrients, or predators, can influence snail abundance and parasite production within infected snails, both components of human risk. This study investigated how snail host abundance and release of cercariae (the free swimming stage infective to humans) varies at water access sites in an endemic region in Senegal, a setting where human schistosomiasis prevalence is among the highest globally. Methods/Principal findings We collected snail intermediate hosts at 15 random points stratified by three habitat types at 36 water access sites, and counted cercarial production by each snail after transfer to the laboratory on the same day. We found that aquatic vegetation was positively associated with per-capita cercarial release by snails, probably because macrophytes harbor periphyton resources that snails feed upon, and well-fed snails tend to produce more parasites. In contrast, the abundance of aquatic macroinvertebrate snail predators was negatively associated with per-capita cercarial release by snails, probably because of several potential sublethal effects on snails or snail infection, despite a positive association between snail predators and total snail numbers at a site, possibly due to shared habitat usage or prey tracking by the predators. Thus, complex bottom-up and top-down ecological effects in this region plausibly influence the snail shedding rate and thus, total local density of schistosome cercariae. Conclusions/Significance Our study suggests that aquatic macrophytes and snail predators can influence per-capita cercarial production and total abundance of snails. Thus, snail control efforts might benefit by targeting specific snail habitats where parasite production is greatest. In conclusion, a better understanding of top-down and bottom-up ecological factors that regulate densities of cercarial release by snails, rather than solely snail densities or snail infection prevalence, might facilitate improved schistosomiasis control., Author summary Over 800 million people are at risk of schistosomiasis and environmental factors that regulate densities of cercariae parasites that infect humans remain poorly understood. We sampled a spatially extensive area at 36 water-access points in northern Senegal, and quantified densities of snail intermediate hosts, snail predators, and aquatic vegetation in each sample, as well as cercariae released from snails after they were brought to the laboratory. We found that the quantity of submerged aquatic vegetation, particularly Ceratophyllum spp., was positively associated with schistosome cercariae released per infected snail, and total potential cercariae released by the collected snails per water access site. In contrast, the abundance of aquatic predators near infected snails (in the same sweep) was negatively associated with the per-capita cercarial release by infected snails, but positively associated with total snail abundance per site. Additionally, snail densities and potential cercarial densities (estimated as the sum of cercariae released by all collected, infected snails at a site) were only weakly correlated, suggesting that snail densities alone might not accurately reflect total potential of those snails to emit schistosome cercariae. Overall, a better understanding of aquatic factors that can influence the production of schistosome cercariae under field conditions, rather than snail host abundance alone, might facilitate improvements in schistosomiasis monitoring and control.

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.

Recent evidence suggests crustacean snail predators may aid schistosomiasis control programs by targeting the environmental component of the parasite’s life cycle through predation of the snail species that serve as intermediate hosts of the parasite. We evaluate costs, benefits, and potential synergies between schistosomiasis control and aquaculture of giant prawns using an integrated bio-economic-epidemiologic model. We identified combinations of stocking density and aquaculture cycle length that maximize profit and offer disease control benefits for sustainable schistosomiasis control. We consider two prawn species in sub-Saharan Africa: the endemic, non-domesticated Macrobrachium vollenhovenii, and the non-native, domesticated Macrobrachium rosenbergii. We find that, at profit-optimal densities, both M. rosenbergii and M. vollenhovenii can complement conventional control approaches (mass drug treatment of people) and lead to sustainable schistosomiasis control. We conclude that integrated aquaculture strategies can be a win-win strategy in terms of health and sustainable development in schistosomiasis endemic regions of the world.

Executive summary: Over the past four decades, rapid urbanisation in China has brought unprecedented health benefits to its urban population, but has also created new challenges for protection of and promotion of health in cities. With the shift from rural to urban living, more people than ever enjoy the health advantages that cities can provide, such as better access to health services and improved sanitation. For example, the average life expectancy of male urban residents in 2010 was estimated to be 7·09 years longer than that of of their counterparts in rural China; urban females lived 6·64 years longer.1 Other changes associated with rapid urbanisation– including large-scale migration, ageing, pollution, shifts in diet and lifestyle, and social inequality–have created new health challenges.2 For example, about 52% of people over 60 years old lived in urban areas in 2015 compared with 34% in 2000,3 thus increasing the burden of senior care in Chinese cities. Non-communicable diseases have replaced infectious diseases as the leading cause of death among urban residents; the percentage of years of life lost because of such diseases as a fraction of all-cause years of life lost increased from 50·0% (95% CI 48·5–53·0) in 1990 to 77·3% (76·5–78·1) in 2015.4 Health inequality also increased in urban areas.5 China has acted to address urban health challenges by passing strict environmental regulations and investing heavily in urban infrastructure. Major reforms have been passed to increase the transparency of environmental governance to control pollution over the short term, while moving to reform whole industries and thus provide long-term solutions. Programmes like the Hygienic Cities movement have invested heavily in urban infrastructure to promote health, including major improvements in urban sanitation.6 China has also increased coverage of and accessibility to health services in urban areas. In 2016, around 93·8% of the urban population was covered by urban medical insurance programmes, a substantial increase from 4·1% in 1998 when the programmes started.7,8 Meanwhile, cities in China are also testing new strategies for urban health management, such as China’s pilot Healthy Cities project.9 Management of chronic diseases and mental disorders in cities has improved dramatically and major progress has been made regarding access to preventive and primary health services. All these efforts have contributed to the reduction of exposure to health risks and health improvement in urban China. However, despite these successes, major gaps remain, including but not limited to an over-reliance on a top-down-approach to environmental management, a narrow focus on health care in urban health management, and a scarcity of intersectoral action. Given that the urbanisation rate in China is predicted to reach 71% by 2030,10 urban health challenges will continue to emerge and expand. If innovative strategies are not used to address these issues, they will become major obstacles to the achievement of improved health and development for millions of people. It has also become clear that the health sector alone, with its traditional piecemeal approach, cannot effectively resolve the modern challenges to urban health in China. The country is now in a transitional period in which the pursuit of economic growth at any cost is being replaced by sustainable development. In 2013, President Xi Jinping declared China’s intention to develop a so-called ecological civilisation (ecocivilisation), the core principles of which involve balancing the relationship between humanity and nature. During this transition, health is recognised as the centrepiece of sustainable development in China, as highlighted in the Healthy China 2030 plan that was adopted in 2016.11 As a result, people-centred and health-oriented urban development will hopefully prevail in China; however, major efforts, political will, and investments will be needed to put this vision into practice. The Tsinghua–Lancet Commission on Healthy Cities in China aimed to characterise, understand, and address urban health challenges in the unique context of China’s rapid and dynamic urban development. Experts from a wide range of disciplines examined environmental and social determinants of health, identified key stakeholders,and assessed actions for the prevention, management, and control of adverse health outcomes associated with the country’s urban experience. We conclude that key efforts are needed to combat urban health challenges in China and these should be unified with the Healthy Cities movement, which uses a systems approach to urban health management and provides a clear path to the realisation of the Healthy China 2030 plan. Actions taken to build healthy cities in China have contributed to global knowledge on the development of healthy cities in other parts of the world. China’s strategic, simultaneous rollout of diverse trials in different cities— in areas such as health education and promotion—and its rapid adoption of effective approaches at the national scale is a valuable lesson for other countries facing rapid urbanisation. Despite such successes, we believe that there is room for substantial improvement and make the following five key recommendations. Integrate health into all policies China should take advantage of new, human-centred urbanisation strategies. For example, cities should integrate health into urban planning and design as a first step towards the integration of health into all policies. Increase participation Cities should increase participation by residents, the private sector, non-governmental organisations (NGOs), and community groups in health management. This increase can be achieved through investment in community capacity building and engagement with the private sector. Promote intersectoral action To motivate and sustain intersectoral action in the design, building, and management of healthy cities, cities should develop ways to assess the health effects of urban management by use of measures that span multiple and diverse sectors. Set local goals for 2030 and assess progress periodically Cities should view the health goals specified in the Healthy China 2030 plan as long-term goals that are achieved through the building of healthy cities. Indicator systems should be put in place to assess progress and inform the public. Enhance research and education on healthy cities To develop new theories and practical solutions, cities should increase investment and form partnerships with universities, research institutes, and the private sector to support research and education on the best ways to create healthy cities.

Rotavirus is considered a directly transmitted disease due to its high infectivity. Environmental pathways have, therefore, largely been ignored. Rotavirus, however, persists in water sources, and both its surface water concentrations and infection incidence vary with temperature. Here, we examine the potential for waterborne rotavirus transmission. We use a mechanistic model that incorporates both direct and waterborne transmission pathways, coupled with a hydrological model, and we simulate rotavirus transmission between two communities with interconnected water sources. To parameterize temperature dependency, we estimated temperature-dependent decay rates in water through a meta-analysis. Our meta-analysis suggests that rotavirus decay rates are positively associated with temperature (n = 39, P [Formula: see text] 0.001). This association is stronger at higher temperatures (over 20 °C), consistent with tropical climate conditions. Our model analysis demonstrates that water could disseminate rotavirus between the two communities for all modeled temperatures. While direct transmission was important for disease amplification within communities, waterborne transmission could also amplify transmission. In standing-water systems, the modeled increase in decay led to decreased disease, with every 1 °C increase in temperature leading to up to a 2.4% decrease in incidence. These effect sizes are consistent with prior meta-analyses, suggesting that environmental transmission through water sources may partially explain the observed associations between temperature and rotavirus incidence. Waterborne rotavirus transmission is likely most important in cooler seasons and in communities that use slow-moving or stagnant water sources. Even when indirect transmission through water cannot sustain outbreaks, it can seed outbreaks that are maintained by high direct transmission rates.

Schistosomiasis is a snail-borne parasitic disease that ranks among the most important water-based diseases of humans in developing countries. Increased prevalence and spread of human schistosomiasis to non-endemic areas has been consistently linked with water resource management related to agricultural expansion. However, the role of agrochemical pollution in human schistosome transmission remains unexplored, despite strong evidence of agrochemicals increasing snail-borne diseases of wildlife and a projected 2- to 5-fold increase in global agrochemical use by 2050. Using a field mesocosm experiment, we show that environmentally relevant concentrations of fertilizer, a herbicide, and an insecticide, individually and as mixtures, increase densities of schistosome-infected snails by increasing the algae snails eat and decreasing densities of snail predators. Epidemiological models indicate that these agrochemical effects can increase transmission of schistosomes. Identifying agricultural practices or agrochemicals that minimize disease risk will be critical to meeting growing food demands while improving human wellbeing., Agrochemicals can affect the life cycle of human parasites in unexpected ways. Here, Halstead et al. show in mesocosm experiments that agrochemicals increase the density of snails hosting schistosome parasites, and modeling analysis suggests this could lead to increased risk of human schistosomiasis.