The prevalence of onchocerciasis in Africa and Yemen, 2000-2018: a geospatial analysis.

BACKGROUND: Onchocerciasis is a disease caused by infection with Onchocerca volvulus, which is transmitted to humans via the bite of several species of black fly, and is responsible for permanent blindness or vision loss, as well as severe skin disease. Predominantly endemic in parts of Africa and Yemen, preventive chemotherapy with mass drug administration of ivermectin is the primary intervention recommended for the elimination of its transmission. METHODS: A dataset of 18,116 geo-referenced prevalence survey datapoints was used to model annual 2000-2018 infection prevalence in Africa and Yemen. Using Bayesian model-based geostatistics, we generated spatially continuous estimates of all-age 2000-2018 onchocerciasis infection prevalence at the 5 × 5-km resolution as well as aggregations to the national level, along with corresponding estimates of the uncertainty in these predictions. RESULTS: As of 2018, the prevalence of onchocerciasis infection continues to be concentrated across central and western Africa, with the highest mean estimates at the national level in Ghana (12.2%, 95% uncertainty interval [UI] 5.0-22.7). Mean estimates exceed 5% infection prevalence at the national level for Cameroon, Central African Republic, Democratic Republic of the Congo (DRC), Guinea-Bissau, Sierra Leone, and South Sudan. CONCLUSIONS: Our analysis suggests that onchocerciasis infection has declined over the last two decades throughout western and central Africa. Focal areas of Angola, Cameroon, the Democratic Republic of the Congo, Ethiopia, Ghana, Guinea, Mali, Nigeria, South Sudan, and Uganda continue to have mean microfiladermia prevalence estimates exceeding 25%. At and above this level, the continuation or initiation of mass drug administration with ivermectin is supported. If national programs aim to eliminate onchocerciasis infection, additional surveillance or supervision of areas of predicted high prevalence would be warranted to ensure sufficiently high coverage of program interventions.

Geographic Pattern of Typhoid Fever in India: A Model-Based Estimate of Cohort and Surveillance Data.

BACKGROUND: Typhoid fever remains a major public health problem in India. Recently, the Surveillance for Enteric Fever in India program completed a multisite surveillance study. However, data on subnational variation in typhoid fever are needed to guide the introduction of the new typhoid conjugate vaccine in India. METHODS: We applied a geospatial statistical model to estimate typhoid fever incidence across India, using data from 4 cohort studies and 6 hybrid surveillance sites from October 2017 to March 2020. We collected geocoded data from the Demographic and Health Survey in India as predictors of typhoid fever incidence. We used a log linear regression model to predict a primary outcome of typhoid incidence. RESULTS: We estimated a national incidence of typhoid fever in India of 360 cases (95% confidence interval [CI], 297-494) per 100 000 person-years, with an annual estimate of 4.5 million cases (95% CI, 3.7-6.1 million) and 8930 deaths (95% CI, 7360-12 260), assuming a 0.2% case-fatality rate. We found substantial geographic variation of typhoid incidence across the country, with higher incidence in southwestern states and urban centers in the north. CONCLUSIONS: There is a large burden of typhoid fever in India with substantial heterogeneity across the country, with higher burden in urban centers.

Stable and Local Reservoirs of Mycobacterium ulcerans Inferred from the Nonrandom Distribution of Bacterial Genotypes, Benin.

Mycobacterium ulcerans is the causative agent of Buruli ulcer, a neglected tropical disease found in rural areas of West and Central Africa. Despite the ongoing efforts to tackle Buruli ulcer epidemics, the environmental reservoir of its pathogen remains elusive, underscoring the need for new approaches to improving disease prevention and management. In our study, we implemented a local-scale spatial clustering model and deciphered the genetic diversity of the bacteria in a small area of Benin where Buruli ulcer is endemic. Using 179 strain samples from West Africa, we conducted a phylogeographic analysis combining whole-genome sequencing with spatial scan statistics. The 8 distinct genotypes we identified were by no means randomly spread over the studied area. Instead, they were divided into 3 different geographic clusters, associated with landscape characteristics. Our results highlight the ability of M. ulcerans to evolve independently and differentially depending on location in a specific ecologic reservoir.

Ridge to Reef Management Implications for the Development of an Open-Source Dissolved Inorganic Nitrogen-Loading Model in American Samoa.

Excessive nutrient discharge to tropical island coastlines drives eutrophication and algal blooms with significant implications for reef ecosystem condition and provision of ecosystem services. Management actions to address nutrient pollution in coastal ecosystems include setting water-quality standards for surface waters discharging to the coast. However, these standards do not account for the effects of groundwater discharge, variability in flow, or dilution, all of which may influence the assessment of true nutrient impacts on nearshore reef habitats. We developed a method to estimate dissolved inorganic nitrogen (DIN) loads to coastal zones by integrating commonly available datasets within a geospatial modeling framework for Tutuila, American Samoa. The DIN-loading model integrated an open-source water budget model, water-sampling results, and publicly available streamflow data to predict watershed-scale DIN loading to the island's entire coastline. Submarine groundwater discharge (SGD) was found to deliver more terrigenous DIN to the coastal zone than surface water pathways, supporting findings from other tropical islands. On-site wastewater disposal systems were also found to be the primary anthropogenic sources of DIN to coastal waters. Our island-wide DIN-loading model provides a simple and robust metric to define spatially explicit sources and delivery mechanisms of nutrient pollution to nearshore reef habitats. Understanding the sources and primary transport modes of inorganic nitrogen to nearshore reef ecosystems can help coastal resource managers target the most impactful human activities in the most vulnerable locations, thereby increasing the adaptive capacity of unique island ecosystems to environmental variation and disturbances.

Understanding heterogeneities in mosquito-bite exposure and infection distributions for the elimination of lymphatic filariasis.

It is well known that individuals in the same community can be exposed to a highly variable number of mosquito bites. This heterogeneity in bite exposure has consequences for the control of vector-borne diseases because a few people may be contributing significantly to transmission. However, very few studies measure sources of heterogeneity in a way which is relevant to decision-making. We investigate the relationship between two classic measures of heterogeneity, spatial and individual, within the context of lymphatic filariasis, a parasitic mosquito-borne disease. Using infection and mosquito-bite data for five villages in Papua New Guinea, we measure biting characteristics to model what impact bed-nets have had on control of the disease. We combine this analysis with geospatial modelling to understand the spatial relationship between disease indicators and nightly mosquito bites. We found a weak association between biting and infection heterogeneity within villages. The introduction of bed-nets increased biting heterogeneity, but the reduction in mean biting more than compensated for this, by reducing prevalence closer to elimination thresholds. Nightly biting was explained by a spatial heterogeneity model, while parasite load was better explained by an individual heterogeneity model. Spatial and individual heterogeneity are qualitatively different with profoundly different policy implications.

Modeled and Perceived Exposure to Radiofrequency Electromagnetic Fields From Mobile-Phone Base Stations and the Development of Symptoms Over Time in a General Population Cohort.

We assessed associations between modeled and perceived exposure to radiofrequency electromagnetic fields (RF-EMF) from mobile-phone base stations and the development of nonspecific symptoms and sleep disturbances over time. A population-based Dutch cohort study, the Occupational and Environmental Health Cohort Study (AMIGO) (n = 14,829; ages 31-65 years), was established in 2011/2012 (T0), with follow-up of a subgroup (n = 3,992 invited) in 2013 (T1; n = 2,228) and 2014 (T2; n = 1,740). We modeled far-field RF-EMF exposure from mobile-phone base stations at the home addresses of the participants using a 3-dimensional geospatial model (NISMap). Perceived exposure (0 = not at all; 6 = very much), nonspecific symptoms, and sleep disturbances were assessed by questionnaire. We performed cross-sectional and longitudinal analyses, including fixed-effects regression. We found small correlations between modeled and perceived exposure in AMIGO participants at baseline (n = 14,309; rSpearman = 0.10). For 222 follow-up participants, modeled exposure increased substantially (>0.030 mW/m2) between T0 and T1. This increase in modeled exposure was associated with an increase in perceived exposure during the same time period. In contrast to modeled RF-EMF exposure from mobile-phone base stations, perceived exposure was associated with higher symptom reporting scores in both cross-sectional and longitudinal analyses, as well as with sleep disturbances in cross-sectional analyses.

How Did the Built Environment Affect Urban Vibrancy? A Big Data Approach to Post-Disaster Revitalization Assessment.

Quantitative assessment of urban vibrancy is crucial to understanding urban development and promoting sustainability, especially for rapidly developing areas and regions that have experienced post-disaster reconstruction. Taking Dujiangyan City, the hardest-hit area of the earthquake, as an example, this paper quantifies the urban economic, social, and cultural vibrancy after reconstruction by the use of multi-source data, and conducts a geographic visualization analysis. The purpose is to establish an evaluation framework for the relationship between the urban built environment elements and vibrancy in different dimensions, to evaluate the benefits of post-disaster restoration and reconstruction. The results show that the urban vibrancy reflected by classified big data can not be completely matched due to the difference in the data generation and collection process. The Criteria Importance Though Inter-criteria Correlation and entropy (CRITIC-entropy) method is used to construct a comprehensive model is a better representation of the urban vibrancy spatial characteristics. On a global scale, comprehensive vibrancy demonstrates high continuity and a bi-center structure. In the old town, the distribution of various urban vibrancies show diffusion characteristics, while those in the new district demonstrated a high degree of aggregation, and the comprehensive vibrancy is less sensitive to land-use mixture and more sensitive to residential land.

Spatiotemporal controls on septic system derived nutrients in a nearshore aquifer and their discharge to a large lake.

This study evaluates spatiotemporal variability in the behavior of septic system derived nutrients in a sandy nearshore aquifer and their discharge to a large lake. A groundwater nutrient-rich plume was monitored over a two-year period with the septic system origin of the plume confirmed using artificial sweeteners. High temporal variability in NO3-N attenuation in the nearshore aquifer prior to discharge to the lake (42-96%) reveals the complex behavior of NO3-N and potential importance of changing hydrological and geochemical conditions in controlling NO3-N discharge to the lake. While PO4-P was retarded in the nearshore aquifer, the PO4-P plume extended over 90 m downgradient of the septic system. It was estimated that the PO4-P plume may reach the lake within 10 years and represents a legacy issue whereby PO4-P loads to the lake may increase over time. To provide broader assessment of the contribution of septic systems to P and N loads to a large lake, a regional scale geospatial model was developed that considers the locations of individual septic systems along the Canadian Lake Erie shoreline. The estimated P and N loads indicate that septic systems along the shoreline are only a minor contributor to the annual P and N loads to Lake Erie. However, it is possible that nutrients from septic systems may contribute to localized algal blooms in shoreline areas with high septic system density. In addition, disproportionate P and N loads in discharging groundwater may change the N:P ratio in nearshore waters and promote growth of harmful cyanobacteria. The study provides new insights into factors controlling the function of the reaction zone near the groundwater-lake interface including its impact on groundwater-derived nutrient inputs to large lakes. Further, the study findings are needed to inform septic system and nutrient management programs aimed at reducing lake eutrophication.

Sobrepeso y obesidad en adultos: aportes de un análisis geoespacial

Objetivo: Realizar un análisis geoespacial del comportamiENTo de sobrepeso y obesidad basado en la "Encuesta Nacional de Situación Nutricional" de 2015. Metodología: Se aplica un modelo de análisis geoespacial de distribución espacial trasversal a partir de la Encuesta, a escala departamENTal. Para lograrlo, se calculan las prevalencias de sobrepeso, obesidad clase i, ii y iii según el índice de masa corporal y la obesidad abdominal en mujeres y hombres de acuerdo con la circunferencia de cintura. Se utilizan herramiENTas de sistemas de información geográfica, como el índice de Moran Global, el índice local de autocorrelación espacial (lisa) y el G* Getis Ord, para determinar los patrones de agrupaciones altas y bajas prevalencias. Resultados: Los conglomerados locales ilustrados en los mapas demuestran que sus residuales están distribuidos normalmENTe en el espacio. Se observa una aleatoriedad en el modelo de la autocorrelación espacial. Las agrupaciones de lisa alta-alta se presENTan en diez departamENTos con estas condiciones (La Guajira, Magdalena, Atlántico, Sucre, Cesar, Norte de Santander, Córdoba, Antioquia, Chocó y Cundinamarca). Según el índice de masa corporal, el 38,5 por cada 100 habitantes tienen sobrepeso; el 20,9 por cada 100 habitantes presENTa obesidad, y según la circunferencia de cintura, 53,2 por cada 100 habitantes tiene obesidad abdominal. Conclusiones: La distribución espacial del sobrepeso y la obesidad puede estar condicionada con variables sociodemográficas tratadas en el estudio. El país tiene el reto de continuar implemENTando acciones poblacionales en salud pública para disminuir estas condiciones.

Objective: To carry out a geospatial analysis of the behavior of overweight and obesity based on the "National Survey of Nutritional Situation" of 2015. Methodology: A geospatial analysis model of transversal spatial distribution is applied from the Survey, on a departmENTal scale. To achieve this, the prevalence of overweight, class I, II and III obesity according to body mass index and abdominal obesity in women and men according to waist circumference are calculated. Geographic information system tools, such as the Global Moran Index, Local Spatial Autocorrelation Index (LISA), and G* Getis Ord, are used to determine patterns of high clustering and low prevalence. Results: The local clusters illustrated on the maps demonstrate that their residuals are normally distributed in space. A randomness is observed in the spatial autocorrelation model. High-high LISA clusters occur in ten departmENTs with these conditions (La Guajira, Magdalena, Atlántico, Sucre, Cesar, Norte de Santander, Córdoba, Antioquia, Chocó and Cundinamarca). According to the body mass index, 38.5 per 100 inhabitants are overweight; 20.9 per 100 inhabitants are obese, and according to waist circumference, 53.2 per 100 inhabitants have abdominal obesity. Conclusions: The spatial distribution of overweight and obesity may be conditioned by the sociodemographic variables treated in the study. The country has the challenge of continuing to implemENT population actions in public health to reduce these conditions.

Objetivo: Realizar uma análise geoespacial do comportamENTo do sobrepeso e da obesidade com base na "Pesquisa Nacional de Situação Nutricional" de 2015. Metodologia: Aplica-se um modelo de análise geoespacial de distribuição espacial transversal da Pesquisa, em escala departamENTal. Para isso, calcula-se a prevalência de sobrepeso, obesidade graus I, II e III segundo o índice de massa corporal e obesidade abdominal em mulheres e homens segundo a circunferência da cintura. As ferramENTas do sistema de informações geográficas, como o Índice de Moran Global, o Índice de Autocorrelação Espacial Local (Smooth) e o G* Getis Ord, são usadas para determinar padrões de alto agrupamENTo e baixa prevalência. Resultados: Os clusters locais ilustrados nos mapas demonstram que seus resíduos são normalmENTe distribuídos no espaço. Uma aleatoriedade é observada no modelo de autocorrelação espacial. Grupos de tainhas alto-alto ocorrem em dez departamENTos com essas condições (La Guajira, Magdalena, Atlântico, Sucre, Cesar, Norte de Santander, Córdoba, Antioquia, Chocó e Cundinamarca). De acordo com o índice de massa corporal, 38,5 por 100 habitantes estão acima do peso; 20,9 por 100 habitantes são obesos e, segundo a circunferência da cintura, 53,2 por 100 habitantes têm obesidade abdominal. Conclusões: A distribuição espacial do sobrepeso e da obesidade pode estar condicionada pelas variáveis sociodemográficas tratadas no estudo. O país tem o desafio de continuar implemENTando ações populacionais em saúde pública para reduzir esses agravos.

Residential exposure to RF-EMF from mobile phone base stations: Model predictions versus personal and home measurements.

INTRODUCTION: Geospatial models have been demonstrated to reliably and efficiently estimate RF-EMF exposure from mobile phone base stations (downlink) at stationary locations with the implicit assumption that this reflects personal exposure. In this study we evaluated whether RF-EMF model predictions at the home address are a good proxy of personal 48h exposure. We furthermore studied potential modification of this association by degree of urbanisation. METHOD: We first used an initial NISMap estimation (at an assumed height of 4.5m) for 9563 randomly selected addresses in order to oversample addresses with higher exposure levels and achieve exposure contrast. We included 47 individuals across the range of potential RF-EMF exposure and used NISMap to re-assess downlink exposure at the home address (at bedroom height). We computed several indicators to determine the accuracy of the NISMap model predictions. We compared residential RF-EMF model predictions with personal 48h, at home, and night-time (0:00-8:00AM) ExpoM3 measurements, and with EME-SPY 140 spot measurements in the bedroom. We obtained information about urbanisation degree and compared the accuracy of model predictions in high and low urbanised areas. RESULTS: We found a moderate Spearman correlation between model predictions and personal 48h (rSp=0.47), at home (rSp=0.49), at night (rSp=0.51) and spot measurements (rSp=0.54). We found no clear differences between high and low urbanised areas (48h: high rSp=0.38, low rSp=0.55, bedroom spot measurements: high rSp=0.55, low rSp=0.50). DISCUSSION: We achieved a meaningful ranking of personal downlink exposure irrespective of degree of urbanisation, indicating that these models can provide a good proxy of personal exposure in areas with varying build-up.