ABSTRACT
Species distribution models (SDMs) are increasingly popular tools for profiling disease risk in ecology, particularly for infectious diseases of public health importance that include an obligate non-human host in their transmission cycle. SDMs can create high-resolution maps of host distribution across geographical scales, reflecting baseline risk of disease. However, as SDM computational methods have rapidly expanded, there are many outstanding methodological questions. Here we address key questions about SDM application, using schistosomiasis risk in Brazil as a case study. Schistosomiasis is transmitted to humans through contact with the free-living infectious stage of Schistosoma spp. parasites released from freshwater snails, the parasite's obligate intermediate hosts. In this study, we compared snail SDM performance across machine learning (ML) approaches (MaxEnt, Random Forest, and Boosted Regression Trees), geographic extents (national, regional, and state), types of presence data (expert-collected and publicly-available), and snail species (Biomphalaria glabrata, B. straminea, and B. tenagophila). We used high-resolution (1km) climate, hydrology, land-use/land-cover (LULC), and soil property data to describe the snails' ecological niche and evaluated models on multiple criteria. Although all ML approaches produced comparable spatially cross-validated performance metrics, their suitability maps showed major qualitative differences that required validation based on local expert knowledge. Additionally, our findings revealed varying importance of LULC and bioclimatic variables for different snail species at different spatial scales. Finally, we found that models using publicly-available data predicted snail distribution with comparable AUC values to models using expert-collected data. This work serves as an instructional guide to SDM methods that can be applied to a range of vector-borne and zoonotic diseases. In addition, it advances our understanding of the relevant environment and bioclimatic determinants of schistosomiasis risk in Brazil.
ABSTRACT
Understanding how natural communities and ecosystems are structured and respond to anthropogenic pressures in a rapidly changing world is key to successful management and conservation. A fundamental but often overlooked biological characteristic of organisms is sex. Sex-based responses are often considered when conducting studies at organismal and population levels, but are rarely investigated in community ecology. Focusing on kelp forests as a model system, and through a review of other marine and terrestrial ecosystems, we found evidence of widespread sex-based variation in species interactions. Sex-based variation in species interactions is expected to affect ecosystem structure and functioning via multiple trophic and nontrophic pathways. Understanding the drivers and consequences of sex-based variation in species interactions can inform more effective management and restoration.
ABSTRACT
The livestock sector contributes almost 11% of Pakistan's GDP and is crucial to 35 million people's livelihoods. Ticks are a major economic threat, as over 80% of livestock, such as bovines, are tick-infested with Hyalomma and Rhipicephalus tick species. Hyalomma anatolicum and Rhipicephalus microplus are the most common tick species collected from livestock, transmitting primarily anaplasmosis, babesiosis, and theileriosis. We aimed to identify the geographical distribution of these two tick species and hot spot areas where the risk of these diseases being transmitted by these ticks is high. Following the PRISMA guideline, two authors conducted an independent review of literature sourced from various databases. We screened 326 research articles published between January 1, 1990, and December 31, 2023, focused on identifying the tick species at the district level. Thirty studies from 75 districts, representing 49.3% of the country's total area, detected at least one tick species through collection from animals. R. microplus was present in 81% (n = 61) and H. anatolicum in 82% (n = 62) of these sampled districts. We employed spatial and conventional statistical methods with Geographic Information Systems (GIS) after mapping the weighted distribution of both ticks (the number of ticks per standard unit of sampling effort). We identified northwestern and northcentral regions of the country as hotspots with the highest tick distribution, which aligned with the documented high prevalence of anaplasmosis, babesiosis, Crimean-Congo hemorrhagic fever (CCHF), and theileriosis in these regions. This underscores the urgent need for robust tick control measures in these districts to safeguard animal health and boost the livestock economy.
Subject(s)
Rhipicephalus , Tick Infestations , Animals , Pakistan/epidemiology , Rhipicephalus/physiology , Cattle , Tick Infestations/epidemiology , Tick Infestations/veterinary , Ixodidae/physiology , Livestock/parasitology , Anaplasmosis/epidemiology , Babesiosis/epidemiologyABSTRACT
The geographical range of schistosomiasis is affected by the ecology of schistosome parasites and their obligate host snails, including their response to temperature. Previous models predicted schistosomiasis' thermal optimum at 21.7 °C, which is not compatible with the temperature in sub-Saharan Africa (SSA) regions where schistosomiasis is hyperendemic. We performed an extensive literature search for empirical data on the effect of temperature on physiological and epidemiological parameters regulating the free-living stages of S. mansoni and S. haematobium and their obligate host snails, i.e., Biomphalaria spp. and Bulinus spp., respectively. We derived nonlinear thermal responses fitted on these data to parameterize a mechanistic, process-based model of schistosomiasis. We then re-cast the basic reproduction number and the prevalence of schistosome infection as functions of temperature. We found that the thermal optima for transmission of S. mansoni and S. haematobium range between 23.1-27.3 °C and 23.6-27.9 °C (95 % CI) respectively. We also found that the thermal optimum shifts toward higher temperatures as the human water contact rate increases with temperature. Our findings align with an extensive dataset of schistosomiasis prevalence in SSA. The refined nonlinear thermal-response model developed here suggests a more suitable current climate and a greater risk of increased transmission with future warming for more than half of the schistosomiasis suitable regions with mean annual temperature below the thermal optimum.
ABSTRACT
Schistosomiasis is a neglected tropical disease caused by Schistosoma parasites. Schistosoma are obligate parasites of freshwater Biomphalaria and Bulinus snails, thus controlling snail populations is critical to reducing transmission risk. As snails are sensitive to environmental conditions, we expect their distribution is significantly impacted by global change. Here, we used machine learning, remote sensing, and 30 years of snail occurrence records to map the historical and current distribution of forward-transmitting Biomphalaria hosts throughout Brazil. We identified key features influencing the distribution of suitable habitat and determined how Biomphalaria habitat has changed with climate and urbanization over the last three decades. Our models show that climate change has driven broad shifts in snail host range, whereas expansion of urban and peri-urban areas has driven localized increases in habitat suitability. Elucidating change in Biomphalaria distribution-while accounting for non-linearities that are difficult to detect from local case studies-can help inform schistosomiasis control strategies.
Subject(s)
Biomphalaria , Climate Change , Ecosystem , Schistosoma mansoni , Schistosomiasis mansoni , Urbanization , Animals , Brazil , Schistosoma mansoni/physiology , Biomphalaria/parasitology , Schistosomiasis mansoni/transmission , Schistosomiasis mansoni/epidemiology , Schistosomiasis mansoni/parasitology , Snails/parasitology , Snails/physiology , HumansABSTRACT
Aedes aegypti mosquitos are the primary vector for dengue, chikungunya, and Zika viruses and tend to breed in small containers of water, with a propensity to breed in small piles of trash and abandoned tires. This study piloted the use of aerial imaging to map and classify potential Ae. aegypti breeding sites with a specific focus on trash, including discarded tires. Aerial images of coastal and inland sites in Kenya were obtained using an unmanned aerial vehicle. Aerial images were reviewed for identification of trash and suspected trash mimics, followed by extensive community walk-throughs to identify trash types and mimics by description and ground photography. An expert panel reviewed aerial images and ground photos to develop a classification scheme and evaluate the advantages and disadvantages of aerial imaging versus walk-through trash mapping. A trash classification scheme was created based on trash density, surface area, potential for frequent disturbance, and overall likelihood of being a productive Ae. aegypti breeding site. Aerial imaging offers a novel strategy to characterize, map, and quantify trash at risk of promoting Ae. aegypti proliferation, generating opportunities for further research on trash associations with disease and trash interventions.
Subject(s)
Aedes , Animals , Kenya , Unmanned Aerial Devices , Breeding , Mosquito VectorsABSTRACT
The geographical range of schistosomiasis is affected by the ecology of schistosome parasites and their obligate host snails, including their response to temperature. Previous models predicted schistosomiasis' thermal optimum at 21.7°C, which is not compatible with the temperature in sub-Saharan Africa (SSA) regions where schistosomiasis is hyperendemic. We performed an extensive literature search for empirical data on the effect of temperature on physiological and epidemiological parameters regulating the free-living stages of S. mansoni and S. haematobium and their obligate host snails, i.e., Biomphalaria spp. and Bulinus spp., respectively. We derived nonlinear thermal responses fitted on these data to parameterize a mechanistic, process-based model of schistosomiasis. We then re-cast the basic reproduction number and the prevalence of schistosome infection as functions of temperature. We found that the thermal optima for transmission of S. mansoni and S. haematobium range between 23.1-27.3°C and 23.6-27.9°C (95% CI) respectively. We also found that the thermal optimum shifts toward higher temperatures as the human water contact rate increases with temperature. Our findings align with an extensive dataset of schistosomiasis prevalence in SSA. The refined nonlinear thermal-response model developed here suggests a more suitable current climate and a greater risk of increased transmission with future warming for more than half of the schistosomiasis suitable regions with mean annual temperature below the thermal optimum.
Subject(s)
Schistosoma haematobium , Schistosoma mansoni , Temperature , Animals , Humans , Schistosoma haematobium/physiology , Schistosoma mansoni/physiology , Africa South of the Sahara/epidemiology , Biomphalaria/parasitology , Schistosomiasis/transmission , Schistosomiasis/epidemiology , Schistosomiasis mansoni/transmission , Schistosomiasis mansoni/epidemiology , Bulinus/parasitology , Schistosomiasis haematobia/transmission , Schistosomiasis haematobia/epidemiology , PrevalenceABSTRACT
Schistosomiasis is a neglected tropical disease caused by Schistosoma parasites. Schistosoma are obligate parasites of freshwater Biomphalaria snails, so controlling snail populations is critical to reducing transmission risk. As snails are sensitive to environmental conditions, we expect their distribution is significantly impacted by global change. Here, we leveraged machine learning, remote sensing, and 30 years of snail occurrence records to map the historical and current distribution of competent Biomphalaria throughout Brazil. We identified key features influencing the distribution of suitable habitat and determined how Biomphalaria habitat has changed with climate and urbanization over the last three decades. Our models show that climate change has driven broad shifts in snail host range, whereas expansion of urban and peri-urban areas has driven localized increases in habitat suitability. Elucidating change in Biomphalaria distribution - while accounting for non-linearities that are difficult to detect from local case studies - can help inform schistosomiasis control strategies.
ABSTRACT
The human burden of environmentally transmitted infectious diseases can depend strongly on ecological factors, including the presence or absence of natural enemies. The marbled crayfish (Procambarus virginalis) is a novel invasive species that can tolerate a wide range of ecological conditions and colonize diverse habitats. Marbled crayfish first appeared in Madagascar in 2005 and quickly spread across the country, overlapping with the distribution of freshwater snails that serve as the intermediate host of schistosomiasis-a parasitic disease of poverty with human prevalence ranging up to 94% in Madagascar. It has been hypothesized that the marbled crayfish may serve as a predator of schistosome-competent snails in areas where native predators cannot and yet no systematic study to date has been conducted to estimate its predation rate on snails. Here, we experimentally assessed marbled crayfish consumption of uninfected and infected schistosome-competent snails (Biomphalaria glabrata and Bulinus truncatus) across a range of temperatures, reflective of the habitat range of the marbled crayfish in Madagascar. We found that the relationship between crayfish consumption and temperature is unimodal with a peak at ~27.5°C. Per-capita consumption increased with body size and was not affected either by snail species or their infectious status. We detected a possible satiation effect, i.e., a small but significant reduction in per-capita consumption rate over the 72-hour duration of the predation experiment. Our results suggest that ecological parameters, such as temperature and crayfish weight, influence rates of consumption and, in turn, the potential impact of the marbled crayfish invasion on snail host populations.
Subject(s)
Biomphalaria , Schistosomatidae , Humans , Animals , Astacoidea , Temperature , Predatory Behavior , SchistosomaABSTRACT
Many communities in low- and middle-income countries globally lack sustainable, cost-effective and mutually beneficial solutions for infectious disease, food, water and poverty challenges, despite their inherent interdependence1-7. Here we provide support for the hypothesis that agricultural development and fertilizer use in West Africa increase the burden of the parasitic disease schistosomiasis by fuelling the growth of submerged aquatic vegetation that chokes out water access points and serves as habitat for freshwater snails that transmit Schistosoma parasites to more than 200 million people globally8-10. In a cluster randomized controlled trial (ClinicalTrials.gov: NCT03187366) in which we removed invasive submerged vegetation from water points at 8 of 16 villages (that is, clusters), control sites had 1.46 times higher intestinal Schistosoma infection rates in schoolchildren and lower open water access than removal sites. Vegetation removal did not have any detectable long-term adverse effects on local water quality or freshwater biodiversity. In feeding trials, the removed vegetation was as effective as traditional livestock feed but 41 to 179 times cheaper and converting the vegetation to compost provided private crop production and total (public health plus crop production benefits) benefit-to-cost ratios as high as 4.0 and 8.8, respectively. Thus, the approach yielded an economic incentive-with important public health co-benefits-to maintain cleared waterways and return nutrients captured in aquatic plants back to agriculture with promise of breaking poverty-disease traps. To facilitate targeting and scaling of the intervention, we lay the foundation for using remote sensing technology to detect snail habitats. By offering a rare, profitable, win-win approach to addressing food and water access, poverty alleviation, infectious disease control and environmental sustainability, we hope to inspire the interdisciplinary search for planetary health solutions11 to the many and formidable, co-dependent global grand challenges of the twenty-first century.
Subject(s)
Agriculture , Ecosystem , Rural Health , Schistosomiasis , Snails , Animals , Child , Humans , Schistosomiasis/epidemiology , Schistosomiasis/prevention & control , Schistosomiasis/transmission , Snails/parasitology , Africa, Western , Fertilizers , Introduced Species , Intestines/parasitology , Fresh Water , Plants/metabolism , Biodiversity , Animal Feed , Water Quality , Crop Production/methods , Public Health , Poverty/prevention & control , Aquatic Organisms/metabolism , Remote Sensing TechnologyABSTRACT
While much progress has been achieved over the last decades, malaria surveillance and control remain a challenge in countries with limited health care access and resources. High-resolution predictions of malaria incidence using routine surveillance data could represent a powerful tool to health practitioners by targeting malaria control activities where and when they are most needed. Here, we investigate the predictors of spatio-temporal malaria dynamics in rural Madagascar, estimated from facility-based passive surveillance data. Specifically, this study integrates climate, land-use, and representative household survey data to explain and predict malaria dynamics at a high spatial resolution (i.e., by Fokontany, a cluster of villages) relevant to health care practitioners. Combining generalized linear mixed models (GLMM) and path analyses, we found that socio-economic, land use and climatic variables are all important predictors of monthly malaria incidence at fine spatial scales, via both direct and indirect effects. In addition, out-of-sample predictions from our model were able to identify 58% of the Fokontany in the top quintile for malaria incidence and account for 77% of the variation in the Fokontany incidence rank. These results suggest that it is possible to build a predictive framework using environmental and social predictors that can be complementary to standard surveillance systems and help inform control strategies by field actors at local scales.
ABSTRACT
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.
Subject(s)
Chlorpyrifos , Insecticides , Palaemonidae , Pyrethrins , Schistosomiasis , Animals , Humans , Insecticides/toxicity , Pyrethrins/toxicity , Schistosomiasis/epidemiology , Schistosomiasis/parasitology , Permethrin , Palaemonidae/physiologyABSTRACT
BACKGROUND: Billions of people living in poverty are at risk of environmentally mediated infectious diseases-that is, pathogens with environmental reservoirs that affect disease persistence and control and where environmental control of pathogens can reduce human risk. The complex ecology of these diseases creates a global health problem not easily solved with medical treatment alone. METHODS: We quantified the current global disease burden caused by environmentally mediated infectious diseases and used a structural equation model to explore environmental and socioeconomic factors associated with the human burden of environmentally mediated pathogens across all countries. FINDINGS: We found that around 80% (455 of 560) of WHO-tracked pathogen species known to infect humans are environmentally mediated, causing about 40% (129â488 of 359â341 disability-adjusted life years) of contemporary infectious disease burden (global loss of 130 million years of healthy life annually). The majority of this environmentally mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections. Rarely, environmentally mediated pathogens can evolve into global pandemics (eg, HIV, COVID-19) affecting even the wealthiest communities. INTERPRETATION: The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals. FUNDING: Bill & Melinda Gates Foundation, National Institutes of Health, National Science Foundation, Alfred P. Sloan Foundation, National Institute for Mathematical and Biological Synthesis, Stanford University, and the US Defense Advanced Research Projects Agency.
Subject(s)
COVID-19 , Communicable Diseases , Global Burden of Disease , Humans , Communicable Diseases/epidemiology , Global Health , Socioeconomic Factors , United StatesABSTRACT
CRISPR gene drives could revolutionize the control of infectious diseases by accelerating the spread of engineered traits that limit parasite transmission in wild populations. Gene drive technology in mollusks has received little attention despite the role of freshwater snails as hosts of parasitic flukes causing 200 million annual cases of schistosomiasis. A successful drive in snails must overcome self-fertilization, a common feature of host snails which could prevents a drive's spread. Here we developed a novel population genetic model accounting for snails' mixed mating and population dynamics, susceptibility to parasite infection regulated by multiple alleles, fitness differences between genotypes, and a range of drive characteristics. We integrated this model with an epidemiological model of schistosomiasis transmission to show that a snail population modification drive targeting immunity to infection can be hindered by a variety of biological and ecological factors; yet under a range of conditions, disease reduction achieved by chemotherapy treatment of the human population can be maintained with a drive. Alone a drive modifying snail immunity could achieve significant disease reduction in humans several years after release. These results indicate that gene drives, in coordination with existing public health measures, may become a useful tool to reduce schistosomiasis burden in selected transmission settings with effective CRISPR construct design and evaluation of the genetic and ecological landscape.
Subject(s)
Gene Drive Technology , Schistosomiasis , Animals , Humans , Clustered Regularly Interspaced Short Palindromic Repeats , Schistosomiasis/epidemiology , Snails/genetics , Snails/parasitology , Fresh Water , China/epidemiologyABSTRACT
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.
Subject(s)
Communicable Disease Control , Sustainable Development , HumansABSTRACT
Humans live in complex socio-ecological systems where we interact with parasites and pathogens that spend time in abiotic and biotic environmental reservoirs (e.g., water, air, soil, other vertebrate hosts, vectors, intermediate hosts). Through a synthesis of published literature, we reviewed the life cycles and environmental persistence of 150 parasites and pathogens tracked by the World Health Organization's Global Burden of Disease study. We used those data to derive the time spent in each component of a pathogen's life cycle, including total time spent in humans versus all environmental stages. We found that nearly all infectious organisms were "environmentally mediated" to some degree, meaning that they spend time in reservoirs and can be transmitted from those reservoirs to human hosts. Correspondingly, many infectious diseases were primarily controlled through environmental interventions (e.g., vector control, water sanitation), whereas few (14%) were primarily controlled by integrated methods (i.e., combining medical and environmental interventions). Data on critical life history attributes for most of the 150 parasites and pathogens were difficult to find and often uncertain, potentially hampering efforts to predict disease dynamics and model interactions between life cycle time scales and infection control strategies. We hope that this synthetic review and associated database serve as a resource for understanding both common patterns among parasites and pathogens and important variability and uncertainty regarding particular infectious diseases. These insights can be used to improve systems-based approaches for controlling environmentally mediated diseases of humans in an era where the environment is rapidly changing.
Subject(s)
Communicable Diseases , Parasitic Diseases , Communicable Diseases/epidemiology , Ecosystem , Global Health , Humans , Parasitic Diseases/epidemiology , WaterABSTRACT
BACKGROUND: Infectious disease risk is driven by three interrelated components: exposure, hazard, and vulnerability. For schistosomiasis, exposure occurs through contact with water, which is often tied to daily activities. Water contact, however, does not imply risk unless the environmental hazard of snails and parasites is also present in the water. By increasing reliance on hazardous activities and environments, socio-economic vulnerability can hinder reductions in exposure to a hazard. We aimed to quantify the contributions of exposure, hazard, and vulnerability to the presence and intensity of Schistosoma haematobium re-infection. METHODOLOGY/PRINCIPAL FINDINGS: In 13 villages along the Senegal River, we collected parasitological data from 821 school-aged children, survey data from 411 households where those children resided, and ecological data from all 24 village water access sites. We fit mixed-effects logistic and negative binomial regressions with indices of exposure, hazard, and vulnerability as explanatory variables of Schistosoma haematobium presence and intensity, respectively, controlling for demographic variables. Using multi-model inference to calculate the relative importance of each component of risk, we found that hazard (Æ©wi = 0.95) was the most important component of S. haematobium presence, followed by vulnerability (Æ©wi = 0.91). Exposure (Æ©wi = 1.00) was the most important component of S. haematobium intensity, followed by hazard (Æ©wi = 0.77). Model averaging quantified associations between each infection outcome and indices of exposure, hazard, and vulnerability, revealing a positive association between hazard and infection presence (OR = 1.49, 95% CI 1.12, 1.97), and a positive association between exposure and infection intensity (RR 2.59-3.86, depending on the category; all 95% CIs above 1). CONCLUSIONS/SIGNIFICANCE: Our findings underscore the linkages between social (exposure and vulnerability) and environmental (hazard) processes in the acquisition and accumulation of S. haematobium infection. This approach highlights the importance of implementing both social and environmental interventions to complement mass drug administration.
Subject(s)
Reinfection/parasitology , Schistosoma haematobium/physiology , Schistosomiasis haematobia/parasitology , Social Vulnerability , Adolescent , Animals , Child , Child, Preschool , Cross-Sectional Studies , Female , Humans , Longitudinal Studies , Male , Reinfection/epidemiology , Reinfection/psychology , Rural Population/statistics & numerical data , Schistosoma haematobium/genetics , Schistosoma haematobium/isolation & purification , Schistosomiasis haematobia/epidemiology , Schistosomiasis haematobia/psychology , Senegal/epidemiology , Vulnerable Populations/statistics & numerical data , Water/parasitologyABSTRACT
Human-mediated changes to natural ecosystems have consequences for both ecosystem and human health. Historically, efforts to preserve or restore 'biodiversity' can seem to be in opposition to human interests. However, the integration of biodiversity conservation and public health has gained significant traction in recent years, and new efforts to identify solutions that benefit both environmental and human health are ongoing. At the forefront of these efforts is an attempt to clarify ways in which biodiversity conservation can help reduce the risk of zoonotic spillover of pathogens from wild animals, sparking epidemics and pandemics in humans and livestock. However, our understanding of the mechanisms by which biodiversity change influences the spillover process is incomplete, limiting the application of integrated strategies aimed at achieving positive outcomes for both conservation and disease management. Here, we review the literature, considering a broad scope of biodiversity dimensions, to identify cases where zoonotic pathogen spillover is mechanistically linked to changes in biodiversity. By reframing the discussion around biodiversity and disease using mechanistic evidence - while encompassing multiple aspects of biodiversity including functional diversity, landscape diversity, phenological diversity, and interaction diversity - we work toward general principles that can guide future research and more effectively integrate the related goals of biodiversity conservation and spillover prevention. We conclude by summarizing how these principles could be used to integrate the goal of spillover prevention into ongoing biodiversity conservation initiatives.
Subject(s)
Ecosystem , Zoonoses , Animals , Animals, Wild , Biodiversity , Conservation of Natural Resources/methods , Humans , Public Health , Zoonoses/epidemiology , Zoonoses/prevention & controlABSTRACT
In recent decades, computer vision has proven remarkably effective in addressing diverse issues in public health, from determining the diagnosis, prognosis, and treatment of diseases in humans to predicting infectious disease outbreaks. Here, we investigate whether convolutional neural networks (CNNs) can also demonstrate effectiveness in classifying the environmental stages of parasites of public health importance and their invertebrate hosts. We used schistosomiasis as a reference model. Schistosomiasis is a debilitating parasitic disease transmitted to humans via snail intermediate hosts. The parasite affects more than 200 million people in tropical and subtropical regions. We trained our CNN, a feed-forward neural network, on a limited dataset of 5,500 images of snails and 5,100 images of cercariae obtained from schistosomiasis transmission sites in the Senegal River Basin, a region in western Africa that is hyper-endemic for the disease. The image set included both images of two snail genera that are relevant to schistosomiasis transmission - that is, Bulinus spp. and Biomphalaria pfeifferi - as well as snail images that are non-component hosts for human schistosomiasis. Cercariae shed from Bi. pfeifferi and Bulinus spp. snails were classified into 11 categories, of which only two, S. haematobium and S. mansoni, are major etiological agents of human schistosomiasis. The algorithms, trained on 80% of the snail and parasite dataset, achieved 99% and 91% accuracy for snail and parasite classification, respectively, when used on the hold-out validation dataset - a performance comparable to that of experienced parasitologists. The promising results of this proof-of-concept study suggests that this CNN model, and potentially similar replicable models, have the potential to support the classification of snails and parasite of medical importance. In remote field settings where machine learning algorithms can be deployed on cost-effective and widely used mobile devices, such as smartphones, these models can be a valuable complement to laboratory identification by trained technicians. Future efforts must be dedicated to increasing dataset sizes for model training and validation, as well as testing these algorithms in diverse transmission settings and geographies.
Subject(s)
Schistosomiasis , Africa, Western , Animals , Humans , Neural Networks, Computer , Schistosoma , Schistosomiasis/epidemiology , SenegalABSTRACT
Pseudomonas aeruginosa (Pa) is a major bacterial pathogen responsible for chronic lung infections in cystic fibrosis patients. Recent work has implicated Pf bacteriophages, nonlytic filamentous viruses produced by Pa, in the chronicity and severity of Pa infections. Pf phages act as structural elements in Pa biofilms and sequester aerosolized antibiotics, thereby contributing to antibiotic tolerance. Consistent with a selective advantage in this setting, the prevalence of Pf-positive (Pf+) bacteria increases over time in these patients. However, the production of Pf phages comes at a metabolic cost to bacteria, such that Pf+ strains grow more slowly than Pf-negative (Pf-) strains in vitro. Here, we use a mathematical model to investigate how these competing pressures might influence the relative abundance of Pf+ versus Pf- strains in different settings. Our model suggests that Pf+ strains of Pa cannot outcompete Pf- strains if the benefits of phage production falls onto both Pf+ and Pf- strains for a majority of parameter combinations. Further, phage production leads to a net positive gain in fitness only at antibiotic concentrations slightly above the MIC (i.e., concentrations for which the benefits of antibiotic sequestration outweigh the metabolic cost of phage production) but which are not lethal for Pf+ strains. As a result, our model suggests that frequent administration of intermediate doses of antibiotics with low decay rates and high killing rates favors Pf+ over Pf- strains. These models inform our understanding of the ecology of Pf phages and suggest potential treatment strategies for Pf+ Pa infections. IMPORTANCE Filamentous phages are a frontier in bacterial pathogenesis, but the impact of these phages on bacterial fitness is unclear. In particular, Pf phages produced by Pa promote antibiotic tolerance but are metabolically expensive to produce, suggesting that competing pressures may influence the prevalence of Pf+ versus Pf- strains of Pa in different settings. Our results identify conditions likely to favor Pf+ strains and thus antibiotic tolerance. This study contributes to a better understanding of the unique ecology of filamentous phages in both environmental and clinical settings and may facilitate improved treatment strategies for combating antibiotic tolerance.