Spatio-temporal cluster analysis of county-based human West Nile virus incidence in the continental United States

Long-term trends and spatial patterns of West Nile Virus emergence in California, 2004-2021

AIMS

West Nile Virus (WNV) has remained a persistent source of vector-borne disease risk in California since first being identified in the state in 2003. The geographic distribution of WNV activity is relatively widespread, but varies considerably across different regions within the state. Spatial variation in human WNV infection depends upon social-ecological factors that influence mosquito populations and virus transmission dynamics. Measuring changes in spatial patterns over time is necessary for uncovering the underlying regional drivers of disease risk.

METHODS AND RESULTS

In this study, we utilized statewide surveillance data to quantify temporal changes and spatial patterns of WNV activity in California. We obtained annual WNV mosquito surveillance data from 2004 through 2021 from the California Arbovirus Surveillance Program. Geographic coordinates for mosquito pools were analysed using a suite of spatial statistics to identify and classify patterns in WNV activity over time.

CONCLUSIONS

We detected clear patterns of non-random WNV risk during the study period, including emerging hot spots in the Central Valley and non-random periods of oscillating WNV risk in Southern and Northern California subregions. Our findings offer new insights into 18 years of spatio-temporal variation in WNV activity across California, which may be used for targeted surveillance efforts and public health interventions.

Spatiotemporal distribution characteristics and influencing factors of the rate of cardiovascular hospitalization in Ganzhou city of China

Aims

The objective of this study was to analyze hospitalization rates for cardiovascular diseases (CVD) in Ganzhou City, Jiangxi Province of China from 2015 to 2020 and to uncover the spatiotemporal distribution characteristics and influencing factors, and thus to provide reference for the prevention and control of CVD and public health resources planning.

Methods

The hospitalization data for CVDs from 2016 to 2020 was obtained from the First Affiliated Hospital of Gannan Medical University, and ArcGIS 10.8, SaTScan 9.5, and Matlab 20.0 were used to analyze the spatial autocorrelation, spatiotemporal scan statistics, and potential affecting factors of the hospitalization rates.

Results

The hospitalization rate for CVDs in Ganzhou City showed a slightly increasing trend from 2016 to 2020, with higher rates in winter and summer than that in spring and autumn, and the individuals aged 61 and above constitute a higher proportion compared to other age groups. Additionally, there was a positive correlation between hospitalization rates for CVDs and the counties and districts in Ganzhou City, with high-high aggregation areas mainly distributed in Nankang District, the western urban area of Ganzhou City. The spatial scan analysis identified three different types of significant aggregation areas: high-risk, low-risk, and middle-risk areas. The high-risk area was mainly centered around Zhanggong District or Shangyu County in the central and western regions, with a disease hospitalization rate 2-3 times higher than the rest areas. The study also found that environmental meteorological factors such as the annual average concentration of NO2, O3, average annual temperature, and annual maximum temperature diurnal range had a significant positive effect on hospitalization rates for CVDs in Ganzhou City, with O3 concentration and average annual temperature having significant positive indirect spatial spillover effects.

Conclusion

Winter and summer are the seasons with high hospitalization rate of cardiovascular diseases. County residents aged 61 and above are the higher-risk population that needs to pay more attention on for prevention and control of CVD in Ganzhou City, which exhibits significant spatiotemporal clustering. The urban areas of Zhanggong and Nankang in Ganzhou City are the key areas for prevention and control of CVD. The hospitalization rate of CVD in Ganzhou City is influenced by the aforementioned four environmental meteorological factors, with the annual maximum temperature diurnal range showing the most significant positive direct effect.

Comparison of West Nile Virus Disease in Humans and Horses: Exploiting Similarities for Enhancing Syndromic Surveillance

West Nile virus (WNV) neuroinvasive disease threatens the health and well-being of horses and humans worldwide. Disease in horses and humans is remarkably similar. The occurrence of WNV disease in these mammalian hosts has geographic overlap with shared macroscale and microscale drivers of risk. Importantly, intrahost virus dynamics, the evolution of the antibody response, and clinicopathology are similar. The goal of this review is to provide a comparison of WNV infection in humans and horses and to identify similarities that can be exploited to enhance surveillance methods for the early detection of WNV neuroinvasive disease.

Temporal and Spatial Synchronicity in West Nile Virus Cases Along the Central Flyway, USA

This study of West Nile virus (WNV) examined the possibility of avian transmission to explain synchronicity in the year-to-year variability of WNV case numbers from Texas northward to the Dakotas, and reasons for the large case numbers on the northern Great Plains. We determined correlation coefficients between annual disease incidence per 100,000 people among states within the Great Plains Region, as well as the Central Flyway. There was spatial and temporal synchronicity, as evidenced by Pearson "r," with values along the core of the Central Flyway (Oklahoma, Kansas, Nebraska, and South Dakota) varying between 0.69 and 0.79. Correlations for North Dakota (r = 0.6), however, were affected by local conditions. The concept of relative amplification is helpful in explaining why northerly states along the Central Flyway have larger annual case numbers per 100,000 than Texas but preserve the temporal signal. States differed in their capacity for amplifying the temporal signal in case numbers. For example, Nebraska, South Dakota, and North Dakota case numbers were commonly amplified relative to Texas, with Oklahoma and Kansas deamplified. Relative amplification factors for all states increased as a function of increasing case numbers in Texas. Thus, increased numbers of initially infected birds in Texas likely led to the rapid intensification of the zoonotic cycle as compared to more typical years. The study also confirmed the importance of winter weather in locally modulating disease cases. North Dakota appeared most impacted by these factors to the extent of reducing WNV case numbers in colder years and years with deep snow.

Both consumptive and non-consumptive effects of predators impact mosquito populations and have implications for disease transmission

Predator-prey interactions influence prey traits through both consumptive and non-consumptive effects, and variation in these traits can shape vector-borne disease dynamics. Meta-analysis methods were employed to generate predation effect sizes by different categories of predators and mosquito prey. This analysis showed that multiple families of aquatic predators are effective in consumptively reducing mosquito survival, and that the survival of Aedes, Anopheles, and Culex mosquitoes is negatively impacted by consumptive effects of predators. Mosquito larval size was found to play a more important role in explaining the heterogeneity of consumptive effects from predators than mosquito genus. Mosquito survival and body size were reduced by non-consumptive effects of predators, but development time was not significantly impacted. In addition, Culex vectors demonstrated predator avoidance behavior during oviposition. The results of this meta-analysis suggest that predators limit disease transmission by reducing both vector survival and vector size, and that associations between drought and human West Nile virus cases could be driven by the vector behavior of predator avoidance during oviposition. These findings are likely to be useful to infectious disease modelers who rely on vector traits as predictors of transmission.

Ensemble ecological niche modeling of West Nile virus probability in Florida

Ecological Niche Modeling is a process by which spatiotemporal, climatic, and environmental data are analyzed to predict the distribution of an organism. Using this process, an ensemble ecological niche model for West Nile virus habitat prediction in the state of Florida was developed. This model was created through the weighted averaging of three separate machine learning models—boosted regression tree, random forest, and maximum entropy—developed for this study using sentinel chicken surveillance and remote sensing data. Variable importance differed among the models. The highest variable permutation value included mean dewpoint temperature for the boosted regression tree model, mean temperature for the random forest model, and wetlands focal statistics for the maximum entropy mode. Model validation resulted in area under the receiver curve predictive values ranging from good [0.8728 (95% CI 0.8422–0.8986)] for the maximum entropy model to excellent [0.9996 (95% CI 0.9988–1.0000)] for random forest model, with the ensemble model predictive value also in the excellent range [0.9939 (95% CI 0.9800–0.9979]. This model should allow mosquito control districts to optimize West Nile virus surveillance, improving detection and allowing for a faster, targeted response to reduce West Nile virus transmission potential.

The exploration of the dispersal of British military families in England following the Strategic Defence and Security Review 2010

Strictly relying on publicly available data, this study depicts and quantifies the spatial pattern of England’s military families with dependent children. England’s Service Pupil Premium for the financial years between 2011 and 2019 is used as a proxy variable to estimate the density of service children at the parliamentary constituency level. Methodologically, the approach allows an assessment of spatial movements of a population or a cohort. The results inform policy makers by providing evidence-based findings about the location of England’s military families and how the distribution has changed between 2011 and 2019. The results show empirical evidence supporting the hypothesis that, at a macro scale, beyond commuting distance, England’s military families are becoming increasingly dispersed. We argue that the findings unveil spatial dynamics that have practical issues of housing, employment, and education regarding military families.

Spatial-temporal clusters of host-seeking Aedes albopictus, Aedes japonicus, and Aedes triseriatus collections in a La Crosse virus endemic county (Knox County, Tennessee, USA)

A bite from a La Crosse virus (LACV) infected Aedes mosquito can cause La Crosse encephalitis (LACE), which is a neuro-invasive disease that disproportionately affects children under the age of 16 in Southern Appalachia. The three vectors for LACV are Aedes albopictus (Skuse), Ae. japonicus (Theobald), and Ae. triseriatus (Say). Localized maps of the geographic distribution of vectors are practical tools for mosquito management personnel to target areas with high mosquito abundance. This study hypothesized that LACV vectors have unique species-specific spatial and temporal clusters. To test this, 44 sites were identified in Knox County, Tennessee for their land use/type. At each site, host-seeking mosquitoes were collected approximately every other week from May-October 2018. Spatial clusters of host-seeking mosquito collections for each of the three mosquito species were investigated using Kulldorff's spatial scan statistic, specifying a retrospective space-time Bernoulli model. Most vector clusters were identified in south-central Knox County while the seasonality of clusters varied by mosquito species. Clusters of Ae. albopictus were observed throughout the entire study period while clusters of Ae. japonicus and Ae. triseriatus only occurred May-June. The findings indicate that the relative abundance of LACV vectors were more abundant in south-central Knox County compared to the rest of the county. Of interest, these clusters spatially overlapped with previous LACE diagnosed cases. These findings are useful in guiding decisions on targeted mosquito control in Knox County and may be applied to other counties within Southern Appalachia.

Retrospective Descriptive Analysis of West Nile Neuroinvasive Disease (WNND) in Northwest Louisiana

Aims

The aim of the study was to describe the presentation characteristics and epidemiology of WNND in Louisiana to improve future recognition of cases and decrease inappropriate antibiotic use. Settings and Design. It was a retrospective descriptive-analytic cohort study. A total of 23 patients with WNND were identified at one tertiary care hospital center in Northwest Louisiana from a retrospective chart review from January 1, 2012 to October 31, 2017.

Results

The median age was 49 years (range: 15–75) for patients with WNND. Of 23 patients diagnosed with WNND, twelve (52%) were diagnosed with encephalitis (WNE), six (26%) were diagnosed with meningitis (WNM), and five (22%) with myelitis (WNME). The common symptoms with WNND were fever in 65%, altered mental status in 61%, headache in 52%, fatigue in 43%, gastrointestinal symptoms in 43%, rigors in 30%, imbalance in 26%, rash in 9%, and seizures in 26% of patients. Most patients presented in the late summer season. The average duration of antibiotics given was six days. The average number of days from the admission to the diagnosis of WNND was nine days (3 to 16 days). Twenty-one (91%) patients survived the infection.

Conclusions

Identifying WNV infection early in its clinical course would help in decreasing inappropriate antibiotic use when patients presented with fever and meningeal symptoms. Performing WNV serology in CSF studies is critical in making the diagnosis.

Spatiotemporal Tools for Emerging and Endemic Disease Hotspots in Small Areas: An Analysis of Dengue and Chikungunya in Barbados, 2013-2016

Dengue fever and other febrile mosquito-borne diseases place considerable health and economic burdens on small island nations in the Caribbean. Here, we used two methods of cluster detection to find potential hotspots of transmission of dengue and chikungunya in Barbados, and to assess the impact of input surveillance data and methodology on observed patterns of risk. Using Moran's I and spatial scan statistics, we analyzed the geospatial and temporal distribution of disease cases and rates across Barbados for dengue fever in 2013-2016, and a chikungunya outbreak in 2014. During years with high numbers of dengue cases, hotspots for cases were found with Moran's I in the south and central regions in 2013 and 2016, respectively. Using smoothed disease rates, clustering was detected in all years for dengue. Hotspots suggesting higher rates were not detected via spatial scan statistics, but coldspots suggesting lower than expected rates of disease activity were found in southwestern Barbados during high case years of dengue. No significant spatiotemporal structure was found in cases during the chikungunya outbreak. Spatial analysis of surveillance data is useful in identifying outbreak hotspots, potentially complementing existing early warning systems. We caution that these methods should be used in a manner appropriate to available data and reflecting explicit public health goals-managing for overall case numbers or targeting anomalous rates for further investigation.

A 15 Year Evaluation of West Nile Virus in Wisconsin: Effects on Wildlife and Human Health

West Nile virus (WNV) is the most important and widespread mosquito-borne virus in the United States (U.S.). WNV has the ability to spread rapidly and effectively, infecting more than 320 bird and mammalian species. An examination of environmental conditions and the health of keystone species may help predict the susceptibility of various habitats to WNV and reveal key risk factors, annual trends, and vulnerable regions. Since 2002, WNV outbreaks in Wisconsin varied by species, place, and time, significantly affected by unique climatic, environmental, and geographical factors. During a 15 year period, WNV was detected in 71 of 72 counties, resulting in 239 human and 1397 wildlife cases. Controlling for population and sampling efforts in Wisconsin, rates of WNV are highest in the western and northwestern rural regions of the state. WNV incidence rates were highest in counties with low human population densities, predominantly wetland, and at elevations greater than 1000 feet. Resources for surveillance, prevention, and detection of WNV were lowest in rural counties, likely resulting in underestimation of cases. Overall, increasing mean temperature and decreasing precipitation showed positive influence on WNV transmission in Wisconsin. This study incorporates the first statewide assessment of WNV in Wisconsin.

Analyzing hemorrhagic fever with renal syndrome in Hubei Province, China: a space-time cube-based approach

Objective

Hemorrhagic fever with renal syndrome (HFRS), a natural–focal infectious disease caused by hantaviruses, resulted in 37 deaths between 2011 and 2015 in Hubei Province, China. HFRS outbreaks are seasonally distributed, exhibiting heterogeneity in space and time. We aimed to identify the spatial and temporal characteristics of HFRS epidemics and their probable influencing factors.

Methods

We used the space–time cube (STC) method to investigate HFRS epidemics in different space–time locations. STC can be used to visualize the trajectories of moving objects (or changing tendencies) in space and time in three dimensions. We applied space–time statistical methods, including space–time hot spot and space–time local outlier analyses, based on a calculated STC model of HFRS cases, to identify spatial and temporal hotspots and outlier distributions. We used the space–time gravity center method to reveal associations between possible factors and HFRS epidemics.

Results

In this research, HFRS cases for each space–time location were defined by the STC model, which can present the dynamic characteristics of HFRS epidemics. The STC model delivered accurate and detailed results for the spatiotemporal patterns of HFRS epidemics.

Conclusion

The methods in this paper can potentially be applied for infectious diseases with similar spatial and temporal patterns.

A systematic review of aberration detection algorithms used in public health surveillance

The algorithms used for detecting anomalies have evolved substantially over the last decade to take advantage of advances in informatics and to accommodate changes in surveillance data. We identified 145 studies since 2007 that evaluated statistical methods used to detect aberrations in public health surveillance data. For each study, we classified the analytic methods and reviewed the evaluation metrics. We also summarized the practical usage of the detection algorithms in public health surveillance systems worldwide. Traditional methods (e.g., control charts, linear regressions) were the focus of most evaluation studies and continue to be used commonly in practice. There was, however, an increase in the number of studies using forecasting methods and studies applying machine learning methods, hidden Markov models, and Bayesian framework to multivariate datasets. Evaluation studies demonstrated improved accuracy with more sophisticated methods, but these methods do not appear to be used widely in public health practice.

A new Seasonal Difference Space-Time Autoregressive Integrated Moving Average (SD-STARIMA) model and spatiotemporal trend prediction analysis for Hemorrhagic Fever with Renal Syndrome (HFRS)

Hemorrhagic fever with renal syndrome (HFRS) is a naturally-occurring, fecally transmitted disease caused by a Hantavirus (HV). It is extremely damaging to human health and results in many deaths annually, especially in Hubei Province, China. One of the primary characteristics of HFRS is the spatiotemporal heterogeneity of its occurrence, with notable seasonal differences. In view of this heterogeneity, the present study suggests that there is a need to focus on trend simulation and the spatiotemporal prediction of HFRS outbreaks. To facilitate this, we constructed a new Seasonal Difference Space-Time Autoregressive Integrated Moving Average (SD-STARIMA) model. The SD-STARIMA model is based on the spatial and temporal characteristics of the Space-Time Autoregressive Integrated Moving Average (STARMA) model first developed by Cliff and Ord in 1974, which has proven useful in modelling the temporal aspects of spatially located data. This model can simulate the trends in HFRS epidemics, taking into consideration both spatial and temporal variations. The SD-STARIMA model is also able to make seasonal difference calculations to eliminate temporally non-stationary problems that are present in the HFRS data. Experiments have demonstrated that the proposed SD-STARIMA model offers notably better prediction accuracy, especially for spatiotemporal series data with seasonal distribution characteristics.

How do social-economic differences in urban areas affect tuberculosis mortality in a city in the tri-border region of Brazil, Paraguay and Argentina

Background

The World Health Organization (WHO) launched the “End TB Strategy”, which aims to reduce tuberculosis (TB) mortality by 95% by 2035, Brazil has made a commitment to this, however, one challenge is achieving the goal in the border region, where the TB situation is more critical. The proposal was to analyse the spatial mortality due to TB and its socio-economic determinants in the general population, around the border areas of Brazil, Paraguay and Argentina, as well as the temporal trend in this region.

Method

This ecological study considered the cases of TB deaths of residents of Foz do Iguaçu (BR), with its units of analysis being the census sectors. The standardized mortality rate was calculated for each area. Socioeconomic variables data were obtained from the 2010 Demographic Census of the Brazilian Institute of Geography and Statistics (IBGE). The scan statistic was applied to calculate the spatial relative risk (RR), considering a 95% confidence interval (CI). Spatial dependence was analysed using the Global Bivariate Moran I and Local Bivariate Moran I (LISA) to test the relationship between the socioeconomic conditions of the urban areas and mortality from TB. Analysis of the temporal trend was also performed using the Prais-Winsten test.

Results

A total of 74 cases of TB death were identified, of which 53 (71.6%) were male and 51 (68.9%) people of white skin colour. The mortality rate ranged from 0.28 to 22.75 cases per 100,000 inhabitants. A spatial relative risk area was identified, RR = 5.07 (95% CI 1.79–14.30). Mortality was associated with: proportion of people of brown skin colour (I: 0.0440, p = 0.033), income (low income I: − 0.0611, p = 0.002; high income I: − 0.0449, p = 0.026) and density of residents (3 and 4 residents, I: 0.0537, p = 0.007; 10 or more residents, I: − 0.0390, p = 0.035). There was an increase in the mortality rate in people of brown skin colour (6.1%; 95% CI = 0.029, 0.093).

Conclusion

Death due to TB was associated with income, race resident density and social conditions. Although the TB mortality rate is stationary in the general population, it is increasing among people of brown skin colour.

Exploring spatial patterns of cardiovascular disease in Sweden between 2000 and 2010

AIMS

Cardiovascular disease (CVD) is one of the leading causes of mortality and morbidity worldwide, including in Sweden. The main aim of this study was to explore the temporal trends and spatial patterns of CVD in Sweden using spatial autocorrelation analyses.

METHODS

The CVD admission rates between 2000 and 2010 throughout Sweden were entered as the input disease data for the analytic processes performed for the Swedish capital, Stockholm, and also for the whole of Sweden. Age-adjusted admission rates were calculated using a direct standardisation approach for men and women, and temporal trends analysis were performed on the standardised rates. Global Moran's I was used to explore the structure of patterns and Anselin's local Moran's I, together with Kulldorff's scan statistic were applied to explore the geographical patterns of admission rates.

RESULTS

The rates followed a spatially clustered pattern in Sweden with differences occurring between sexes. Accordingly, hot spots were identified in northern Sweden, with higher intensity identified for men, together with clusters in central Sweden. Cold spots were identified in the adjacency of the three major Swedish cities of Stockholm, Gothenburg and Malmö.

CONCLUSIONS

The findings of this study can serve as a basis for distribution of health-care resources, preventive measures and exploration of aetiological factors.

DETERMINING RAPTOR SPECIES AND TISSUE SENSITIVITY FOR IMPROVED WEST NILE VIRUS SURVEILLANCE

Raptors are a target sentinel species for West Nile virus (WNV) because many are susceptible to WNV disease, they are easily sighted because of their large size, and they often occupy territories near human settlements. Sick and dead raptors accumulate at raptor and wildlife rehabilitation clinics. However, investigations into species selection and specimen type for efficient detection of WNV are lacking. Accordingly, we evaluated dead raptors from north-central Colorado, US and southeast Wyoming, US over a 4-yr period. Nonvascular mature feathers ("quill"), vascular immature feathers ("pulp"), oropharyngeal swabs, cloacal swabs, and kidney samples were collected from raptor carcasses at the Rocky Mountain Raptor Program in Colorado from 2013 through 2016. We tested the samples using real-time reverse transcriptase-PCR. We found that 11% (53/482) of raptor carcasses tested positive for WNV infection. We consistently detected positive specimens during a 12-wk span between the second week of July and the third week of September across all years of the study. We detected WNV RNA most frequently in vascular feather pulp from Cooper's Hawk ( Accipiter cooperii). North American avian mortality surveillance for WNV using raptors can obviate necropsies by selecting Cooper's Hawk and Red-tailed Hawk ( Buteo jamaicensis) as sentinels and targeting feather pulp as a substrate for viral detection.

Spatio-Temporal Pattern and Influencing Factors of Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) between 2005 and 2014

Hemorrhagic Fever with Renal Syndrome (HFRS) is considered as a globally distributed infectious disease, which results in many deaths annually in Hubei Province, China. The outbreak of HFRS is usually characterized with spatio-temporal heterogeneity and is seasonally distributed. Further, it might also be impacted by the influencing factors such as socio-economic and geographical environment. To better understand and predict the outbreak of HFRS in the Hubei Province, the spatio-temporal pattern and influencing factors were investigated in this study. Moran's I Index value was adopted in spatial global autocorrelation analysis to identify the overall spatio-temporal pattern of HFRS outbreak. Kulldorff scan statistical analysis was performed to further identify the changing trends of the clustering patterns of HFRS outbreak. Spearman's rank correlation analysis was used to explore the possible influencing factors on HFRS epidemics such as climate and geographic. The results demonstrated that HFRS outbreak in Hubei Province decreased from 2005 to 2012 in general while increasing slightly from 2012 to 2014. The spatial and temporal scan statistical analysis indicated that HFRS epidemic was temporally clustered in summer and autumn from 2005 to 2014 except 2008 and 2011. The seasonal epidemic pattern of HFRS in Hubei Province was characterized by a bimodal pattern (March to May and September to November) while peaks often occurring in the spring time. SEOV-type HFRS was presumed to influence more on the total number of HFRS incidence than HTNV-type HFRS do. The average humidity and human population density were the main influencing factors during these years. HFRS outbreaks were more in plains than in other areas of Hubei Province. We did not find that whether the terrain of the wetland (water system) plays a significant role in the outbreak of HFRS incidence. With a better understanding of rodent infection rate, socio-economic status and ecological environment characteristics, this study may help to reduce the outbreak of HFRS disease.

Construction of a Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) Model and Comparative Analysis with GWR-Based Models for Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China)

Hemorrhagic fever with renal syndrome (HFRS) is considered a globally distributed infectious disease which results in many deaths annually in Hubei Province, China. In order to conduct a better analysis and accurately predict HFRS incidence in Hubei Province, a new model named Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) was constructed. The SD-GTWR model, which integrates the analysis and relationship of seasonal difference, spatial and temporal characteristics of HFRS (HFRS was characterized by spatiotemporal heterogeneity and it is seasonally distributed), was designed to illustrate the latent relationships between the spatio-temporal pattern of the HFRS epidemic and its influencing factors. Experiments from the study demonstrated that SD-GTWR model is superior to traditional models such as GWR- based models in terms of the efficiency and the ability of providing influencing factor analysis.

Heterogeneity of Mosquito (Diptera: Culicidae) Control Community Size, Research Productivity, and Arboviral Diseases Across the United States

Multiple factors lead to extensive variation in mosquito and mosquito-borne virus control programs throughout the United States. This variation is related to differences in budgets, number of personnel, operational activities targeting nuisance or vector species, integration of Geographical Information Systems, and the degree of research and development to improve management interventions through collaboration with academic institutions. To highlight this heterogeneity, the current study evaluates associations among the size of a mosquito control community, the research productivity, and the mosquito-borne virus human disease burden among states within the continental United States. I used the attendance at state mosquito and vector control meetings as a proxy for the size of the mosquito control community in each state. To judge research productivity, I used all peer-reviewed publications on mosquitoes and mosquito-borne viruses using data originating in each state over a 5- and 20-yr period. Total neuroinvasive human disease cases caused by mosquito-borne viruses were aggregated for each state. These data were compared directly and after adjusting for differences in human population size for each state. Results revealed that mean meeting attendance was positively correlated with the number of publications in each state, but not after correcting for the size of the population in each state. Additionally, human disease cases were positively correlated with the number of publications in each state. Finally, mean meeting attendance and human disease cases were only marginally positively associated, and no correlation existed after correcting for human population size. These analyses indicated that the mosquito control community size, research productivity, and mosquito-borne viral human disease burden varied greatly among states. The mechanisms resulting in this variation were discussed and the consequences of this variation are important given the constantly changing environment due to invasive mosquito species and arboviruses, urbanization, immigration, global travel, and climate change.

Spatio-Temporal Identification of Areas Suitable for West Nile Disease in the Mediterranean Basin and Central Europe

West Nile virus (WNV) is a mosquito-transmitted Flavivirus belonging to the Japanese encephalitis antigenic complex of the Flaviviridae family. Its spread in the Mediterranean basin and the Balkans poses a significant risk to human health and forces public health officials to constantly monitor the virus transmission to ensure prompt application of preventive measures. In this context, predictive tools indicating the areas and periods at major risk of WNV transmission are of paramount importance. Spatial analysis approaches, which use environmental and climatic variables to find suitable habitats for WNV spread, can enhance predictive techniques. Using the Mahalanobis Distance statistic, areas ecologically most suitable for sustaining WNV transmission were identified in the Mediterranean basin and Central Europe. About 270 human and equine clinical cases notified in Italy, Greece, Portugal, Morocco, and Tunisia, between 2008 and 2012, have been considered. The environmental variables included in the model were altitude, slope, night time Land Surface Temperature, Normalized Difference Vegetation Index, Enhanced Vegetation Index, and daily temperature range. Seasonality of mosquito population has been modelled and included in the analyses to produce monthly maps of suitable areas for West Nile Disease. Between May and July, the most suitable areas are located in Tunisia, Libya, Egypt, and North Cyprus. Summer/Autumn months, particularly between August and October, characterize the suitability in Italy, France, Spain, the Balkan countries, Morocco, North Tunisia, the Mediterranean coast of Africa, and the Middle East. The persistence of suitable conditions in December is confined to the coastal areas of Morocco, Tunisia, Libya, Egypt, and Israel.

The ecological foundations of transmission potential and vector-borne disease in urban landscapes

Urban transmission of arthropod-vectored disease has increased in recent decades. Understanding and managing transmission potential in urban landscapes requires integration of sociological and ecological processes that regulate vector population dynamics, feeding behavior, and vector-pathogen interactions in these unique ecosystems. Vectorial capacity is a key metric for generating predictive understanding about transmission potential in systems with obligate vector transmission. This review evaluates how urban conditions, specifically habitat suitability and local temperature regimes, and the heterogeneity of urban landscapes can influence the biologically-relevant parameters that define vectorial capacity: vector density, survivorship, biting rate, extrinsic incubation period, and vector competence.Urban landscapes represent unique mosaics of habitat. Incidence of vector-borne disease in urban host populations is rarely, if ever, evenly distributed across an urban area. The persistence and quality of vector habitat can vary significantly across socio-economic boundaries to influence vector species composition and abundance, often generating socio-economically distinct gradients of transmission potential across neighborhoods.Urban regions often experience unique temperature regimes, broadly termed urban heat islands (UHI). Arthropod vectors are ectothermic organisms and their growth, survival, and behavior are highly sensitive to environmental temperatures. Vector response to UHI conditions is dependent on regional temperature profiles relative to the vector's thermal performance range. In temperate climates UHI can facilitate increased vector development rates while having countervailing influence on survival and feeding behavior. Understanding how urban heat island (UHI) conditions alter thermal and moisture constraints across the vector life cycle to influence transmission processes is an important direction for both empirical and modeling research.There remain persistent gaps in understanding of vital rates and drivers in mosquito-vectored disease systems, and vast holes in understanding for other arthropod vectored diseases. Empirical studies are needed to better understand the physiological constraints and socio-ecological processes that generate heterogeneity in critical transmission parameters, including vector survival and fitness. Likewise, laboratory experiments and transmission models must evaluate vector response to realistic field conditions, including variability in sociological and environmental conditions.

Regional variation of climatic influences on West Nile virus outbreaks in the United States

The national resurgence of human West Nile virus (WNV) disease in 2012 raised questions about the factors responsible for WNV outbreaks. Interannual climatic variations may influence WNV amplification and transmission to humans through multiple pathways, including mosquito breeding habitats, gonotrophic cycles, extrinsic incubation, avian communities, and human behavior. We examined the influences of temperature and precipitation anomalies on interannual variation in human WNV cases in three regions of the United States. There were consistent positive influences of winter temperatures, weaker and more variable positive effects of spring and summer temperatures, and highly variable precipitation effects that ranged from positive to negative. The overwintering period may be a particularly important climatic constraint on the dynamics of WNV in cold-temperate regions of North America. Geographic differences in the seasonal timing and relative importance of climatic drivers of WNV risk likely reflect underlying variability in key ecological and social characteristics.

The identification of 'hotspots' of heavy metal pollution in soil-rice systems at a regional scale in eastern China

Chinese agricultural soils and crops are suffering from increasing damage from heavy metals, which are introduced from various pollution sources including agriculture, traffic, mining and especially the flourishing private metal recycling industry. In this study, 219 pairs of rice grain and corresponding soil samples were collected from Wenling in Zhejiang Province to identify the spatial relationship and pollution hotspots of Cd, Cu, Ni and Zn in the soil-rice system. The mean soil concentrations of heavy metals were 0.316 mg kg(-1) for Cd, 47.3 mg kg(-1) for Cu, 31.7 mg kg(-1) for Ni and 131 mg kg(-1) for Zn, and the metal concentrations in rice grain were 0.132 mg kg(-1) for Cd, 2.46 mg kg(-1) for Cu, 0.223 mg kg(-1) for Ni and 17.4 mg kg(-1) for Zn. The coefficient of variability (CV) of soil Cd, Cu and rice Cd were 147%, 146% and 180%, respectively, indicating an extensive variability. While the CVs of other metals ranged from 23.4% to 84.3% with a moderate variability. Kriging interpolation procedure and the Local Moran's I index detected the locations of pollution hotspots of these four metals. Cd and Cu had a very similar spatial pattern, with contamination hotspots located simultaneously in the northwestern part of the study area, and there were obvious hotspots for soil Zn in the north area, while in the northeast for soil Ni. The existence of hotspots may be due to industrialization and other anthropogenic activities. An Enrichment Index (EI) was employed to measure the uptake of heavy metals by rice. The results indicated that the accumulation and availability of heavy metals in the soil-rice system may be influenced by both soil heavy metal concentrations and soil physico-chemical properties. Cross-correlograms quantitatively illustrated that EIs were significantly correlated with soil properties. Soil pH and organic matter were the most important factors controlling the uptake of heavy metals by rice. As results, positive measures should be taken into account to control soil pollution and to curtail metal contamination to the food chain in the areas of Wenling, which were the most polluted by toxic metals.

Dynamics of spatial clustering of schistosomiasis in the Yangtze River Valley at the end of and following the World Bank Loan Project

The 10-year (1992-2001) World Bank Loan Project (WBLP) contributed greatly to schistosomiasis control in China. However, the re-emergence of schistosomiasis in recent years challenged the long-term progress of the WBLP strategy. In order to gain insight in the long-term progress of the WBLP, the spatial pattern of the epidemic was investigated in the Yangtze River Valley between 1999-2001 and 2007-2008. Two spatial cluster methods were jointly used to identify spatial clusters of cases. The magnitude and number of clusters varied during 1999-2001. It was found that prevalence of schistosomiasis had been greatly reduced and maintained at a low level during 2007-2008, with little change. Besides, spatial clusters most frequently occurred within 16 counties in the Dongting Lake region and within 5 counties in the Poyang Lake region. These findings precisely pointed out the prior places for future public health planning and resource allocation of schistosomiasis.

Changing patterns of spatial clustering of schistosomiasis in Southwest China between 1999-2001 and 2007-2008: assessing progress toward eradication after the World Bank Loan Project

We compared changes in the spatial clustering of schistosomiasis in Southwest China at the conclusion of and six years following the end of the World Bank Loan Project (WBLP), the control strategy of which was focused on the large-scale use of chemotherapy. Parasitological data were obtained through standardized surveys conducted in 1999–2001 and again in 2007–2008. Two alternate spatial cluster methods were used to identify spatial clusters of cases: Anselin’s Local Moran’s I test and Kulldorff’s spatial scan statistic. Substantial reductions in the burden of schistosomiasis were found after the end of the WBLP, but the spatial extent of schistosomiasis was not reduced across the study area. Spatial clusters continued to occur in three regions: Chengdu Plain, Yangtze River Valley, and Lancang River Valley during the two periods, and regularly involved five counties. These findings suggest that despite impressive reductions in burden, the hilly and mountainous regions of Southwest China remain at risk of schistosome re-emergence. Our results help to highlight specific locations where integrated control programs can focus to speed the elimination of schistosomiasis in China.

Spatio-temporal epidemiology of human West Nile virus disease in South Dakota

Despite a cold temperate climate and low human population density, the Northern Great Plains has become a persistent hot spot for human West Nile virus (WNV) disease in North America. Understanding the spatial and temporal patterns of WNV can provide insights into the epidemiological and ecological factors that influence disease emergence and persistence. We analyzed the 1,962 cases of human WNV disease that occurred in South Dakota from 2002-2012 to identify the geographic distribution, seasonal cycles, and interannual variability of disease risk. The geographic and seasonal patterns of WNV have changed since the invasion and initial epidemic in 2002-2003, with cases shifting toward the eastern portion of South Dakota and occurring earlier in the transmission season in more recent years. WNV cases were temporally autocorrelated at lags of up to six weeks and early season cumulative case numbers were correlated with seasonal totals, indicating the possibility of using these data for short-term early detection of outbreaks. Epidemiological data are likely to be most effective for early warning of WNV virus outbreaks if they are integrated with entomological surveillance and environmental monitoring to leverage the strengths and minimize the weaknesses of each information source.

Exploring the spatio-temporal dynamics of reservoir hosts, vectors, and human hosts of West Nile virus: a review of the recent literature

Over the last two decades West Nile Virus (WNV) has been responsible for significant disease outbreaks in humans and animals in many parts of the World. Its extremely rapid global diffusion argues for a better understanding of its geographic extent. The purpose of this inquiry was to explore spatio-temporal patterns of WNV using geospatial technologies to study populations of the reservoir hosts, vectors, and human hosts, in addition to the spatio-temporal interactions among these populations. Review of the recent literature on spatial WNV disease risk modeling led to the conclusion that numerous environmental factors might be critical for its dissemination. New Geographic Information Systems (GIS)-based studies are monitoring occurrence at the macro-level, and helping pinpoint areas of occurrence at the micro-level, where geographically-targeted, species-specific control measures are sometimes taken and more sophisticated methods of surveillance have been used.

Spatial analysis of primary and secondary syphilis incidence in China, 2004-2010

China has recently experienced an increase in the incidence of syphilis. Effective spatial monitoring of syphilis incidence is important for successful implementation of control and prevention programmes. This study monitored county-level primary and secondary (P&S) syphilis incidence rates for all of mainland China by examining spatial patterns. Exploratory spatial data analysis (ESDA) methods were used to characterize the spatial distribution pattern of syphilis cases. During the seven-year study period, the average annual P&S syphilis incidence was 8.82 cases per 100,000 people. Using Empirical Bayes smoothed rates, the local Moran test identified many areas of high syphilis risk (all P values ≤0.01). The number of high-risk counties increased from 73 counties in 2004 to 134 counties in 2010. An eastern coastal cluster of high-risk counties persisted throughout 2004-2010. ESDA methods can assist public health officials in identifying high-risk areas. Allocating more resources to high-risk areas could more effectively reduce syphilis incidence.

Geographical analysis of the distribution and spread of human rabies in china from 2005 to 2011

Background

Rabies is a significant public health problem in China in that it records the second highest case incidence globally. Surveillance data on canine rabies in China is lacking and human rabies notifications can be a useful indicator of areas where animal and human rabies control could be integrated. Previous spatial epidemiological studies lacked adequate spatial resolution to inform targeted rabies control decisions. We aimed to describe the spatiotemporal distribution of human rabies and model its geographical spread to provide an evidence base to inform future integrated rabies control strategies in China.

Methods

We geo-referenced a total of 17,760 human rabies cases of China from 2005 to 2011. In our spatial analyses we used Gaussian kernel density analysis, average nearest neighbor distance, Spatial Temporal Density-Based Spatial Clustering of Applications with Noise and developed a model of rabies spatiotemporal spread.

Findings

Human rabies cases increased from 2005 to 2007 and decreased during 2008 to 2011 companying change of the spatial distribution. The ANN distance among human rabies cases increased between 2005 and 2011, and the degree of clustering of human rabies cases decreased during that period. A total 480 clusters were detected by ST-DBSCAN, 89.4% clusters initiated before 2007. Most of clusters were mainly found in South of China. The number and duration of cluster decreased significantly after 2008. Areas with the highest density of human rabies cases varied spatially each year and in some areas remained with high outbreak density for several years. Though few places have recovered from human rabies, most of affected places are still suffering from the disease.

Conclusion

Human rabies in mainland China is geographically clustered and its spatial extent changed during 2005 to 2011. The results provide a scientific basis for public health authorities in China to improve human rabies control and prevention program.

Estimating West Nile virus transmission period in Pennsylvania using an optimized degree-day model

Abstract We provide calibrated degree-day models to predict potential West Nile virus (WNV) transmission periods in Pennsylvania. We begin by following the standard approach of treating the degree-days necessary for the virus to complete the extrinsic incubation period (EIP), and mosquito longevity as constants. This approach failed to adequately explain virus transmission periods based on mosquito surveillance data from 4 locations (Harrisburg, Philadelphia, Pittsburgh, and Williamsport) in Pennsylvania from 2002 to 2008. Allowing the EIP and adult longevity to vary across time and space improved model fit substantially. The calibrated models increase the ability to successfully predict the WNV transmission period in Pennsylvania to 70-80% compared to less than 30% in the uncalibrated model. Model validation showed the optimized models to be robust in 3 of the locations, although still showing errors for Philadelphia. These models and methods could provide useful tools to predict WNV transmission period from surveillance datasets, assess potential WNV risk, and make informed mosquito surveillance strategies.

West Nile virus infection rates and avian serology in east-central Illinois

Understanding the geographic role of different species of mosquito vectors and vertebrate hosts in West Nile virus (WNV) transmission cycles can facilitate the development and implementation of targeted surveillance and control measures. This study examined the relationship between WNV-antibody rates in birds and mosquito infection rates and bloodfeeding patterns in east-central Illinois. The earliest detection of WNV-RNA by reverse transcription-polymerase chain reaction TaqMan was from Culex restuans; however, amplification typically coincided with an increase in abundance of Cx. pipiens. Trap type influenced annual estimates of infection rates in Culex species, as well as estimation of blood meal source. Bird species with the highest WNV-antibody rates (i.e., Mourning Doves [Zenaida macroura], Northern Cardinals [Cardinalis cardinalis], American Robins [Turdus migratorius], and House Sparrows [Passer domesticus]) were also the common species found in Culex blood meals. Although antibody rates were not directly proportional to estimated avian abundance, the apparent availability of mammal species did influence proportion of mammal to bird blood meals. Antibody prevalence in the American Robin was lower than expected based on the strong attraction of Culex to American Robins for blood meals. Age-related differences in serology were evident, antibody rates increased in older groups of robins and sparrows, whereas 1st-year hatch and older adults of Mourning Doves and Northern Cardinals had equally high rates of antibody-positive serum samples. The vector and host interactions observed in east-central Illinois (Champaign County), an urban area surrounded by agriculture, are compared to studies in the densely population areas of southern Cook County.

West Nile virus outbreak in Phoenix, Arizona--2010: entomological observations and epidemiological correlations

In 2010, Arizona experienced an unusually early and severe outbreak of West Nile virus (WNV) centered in the southeast section of Maricopa County. Entomological data were collected before and during the outbreak, from May 25 through July 31, 2010, using the CO2-baited light trap monitoring system maintained by Maricopa County Vector Control. In the outbreak area, the most abundant species in the Town of Gilbert and in the area covered by the Roosevelt Water Conservation District was Culex quinquefasciatus, constituting 75.1% and 71.8% of the total number of mosquitoes collected, respectively. Vector index (VI) profiles showed that the abundance of infected Cx. quinquefasciatus peaked prior to human cases, suggesting that this species was involved in the initiation of the outbreak. In contrast, the VI profiles for Cx. tarsalis were consistently low, suggesting limited involvement in initiating and sustaining transmission. Taken together, the higher abundance and the VI profiles strongly suggest that Cx. quinquefasciatus was the primary vector for this outbreak. The VI profiles consistently showed that the abundance of infected mosquitoes peaked 1 to 2 wk before the peaks of human cases, suggesting that VI could have successfully been utilized to predict the WNV outbreak in Maricopa County, AZ, in 2010.

Using statistical methods and genotyping to detect tuberculosis outbreaks

Background

Early identification of outbreaks remains a key component in continuing to reduce the burden of infectious disease in the United States. Previous studies have applied statistical methods to detect unexpected cases of disease in space or time. The objectives of our study were to assess the ability and timeliness of three spatio-temporal methods to detect known outbreaks of tuberculosis.

Methods

We used routinely available molecular and surveillance data to retrospectively assess the effectiveness of three statistical methods in detecting tuberculosis outbreaks: county-based log-likelihood ratio, cumulative sums, and a spatial scan statistic.

Results

Our methods identified 8 of the 9 outbreaks, and 6 outbreaks would have been identified 1–52 months (median = 10 months) before local public health authorities identified them. Assuming no delays in data availability, 46 (59.7%) of the 77 patients in the 9 outbreaks were identified after our statistical methods would have detected the outbreak but before local public health authorities became aware of the problem.

Conclusions

Statistical methods, when applied retrospectively to routinely collected tuberculosis data, can successfully detect known outbreaks, potentially months before local public health authorities become aware of the problem. The three methods showed similar results; no single method was clearly superior to the other two. Further study to elucidate the performance of these methods in detecting tuberculosis outbreaks will be done in a prospective analysis.

Dengue fever occurrence and vector detection by larval survey, ovitrap and MosquiTRAP: a space-time clusters analysis

The use of vector surveillance tools for preventing dengue disease requires fine assessment of risk, in order to improve vector control activities. Nevertheless, the thresholds between vector detection and dengue fever occurrence are currently not well established. In Belo Horizonte (Minas Gerais, Brazil), dengue has been endemic for several years. From January 2007 to June 2008, the dengue vector Aedes (Stegomyia) aegypti was monitored by ovitrap, the sticky-trap MosquiTRAP™ and larval surveys in an study area in Belo Horizonte. Using a space-time scan for clusters detection implemented in SaTScan software, the vector presence recorded by the different monitoring methods was evaluated. Clusters of vectors and dengue fever were detected. It was verified that ovitrap and MosquiTRAP vector detection methods predicted dengue occurrence better than larval survey, both spatially and temporally. MosquiTRAP and ovitrap presented similar results of space-time intersections to dengue fever clusters. Nevertheless ovitrap clusters presented longer duration periods than MosquiTRAP ones, less acuratelly signalizing the dengue risk areas, since the detection of vector clusters during most of the study period was not necessarily correlated to dengue fever occurrence. It was verified that ovitrap clusters occurred more than 200 days (values ranged from 97.0±35.35 to 283.0±168.4 days) before dengue fever clusters, whereas MosquiTRAP clusters preceded dengue fever clusters by approximately 80 days (values ranged from 65.5±58.7 to 94.0±14. 3 days), the former showing to be more temporally precise. Thus, in the present cluster analysis study MosquiTRAP presented superior results for signaling dengue transmission risks both geographically and temporally. Since early detection is crucial for planning and deploying effective preventions, MosquiTRAP showed to be a reliable tool and this method provides groundwork for the development of even more precise tools.

Landscape-level spatial patterns of West Nile virus risk in the northern Great Plains

Understanding the landscape-level determinants of West Nile virus (WNV) can aid in mapping high-risk areas and enhance disease control and prevention efforts. This study analyzed the spatial patterns of human WNV cases in three areas in South Dakota during 2003-2007 and investigated the influences of land cover, hydrology, soils, irrigation, and elevation by using case-control models. Land cover, hydrology, soils, and elevation all influenced WNV risk, although the main drivers were different in each study area. Risk for WNV was generally higher in areas with rural land cover than in developed areas, and higher close to wetlands or soils with a high ponding frequency. In western South Dakota, WNV risk also decreased with increasing elevation and was higher in forested areas. Our results showed that the spatial patterns of human WNV risk were associated with landscape-level features that likely reflect variability in mosquito ecology, avian host communities, and human activity.

Under-five mortality in high focus states in India: a district level geospatial analysis

BACKGROUND

This paper examines if, when controlling for biophysical and geographical variables (including rainfall, productivity of agricultural lands, topography/temperature, and market access through road networks), socioeconomic and health care indicators help to explain variations in the under-five mortality rate across districts from nine high focus states in India. The literature on this subject is inconclusive because the survey data, upon which most studies of child mortality rely, rarely include variables that measure these factors. This paper introduces these variables into an analysis of 284 districts from nine high focus states in India.

METHODOLOGY/PRINCIPAL FINDINGS

Information on the mortality indicator was accessed from the recently conducted Annual Health Survey of 2011 and other socioeconomic and geographic variables from Census 2011, District Level Household and Facility Survey (2007-08), Department of Economics and Statistics Divisions of the concerned states. Displaying high spatial dependence (spatial autocorrelation) in the mortality indicator (outcome variable) and its possible predictors used in the analysis, the paper uses the Spatial-Error Model in an effort to negate or reduce the spatial dependence in model parameters. The results evince that the coverage gap index (a mixed indicator of district wise coverage of reproductive and child health services), female literacy, urbanization, economic status, the number of newborn care provided in Primary Health Centers in the district transpired as significant correlates of under-five mortality in the nine high focus states in India. The study identifies three clusters with high under-five mortality rate including 30 districts, and advocates urgent attention.

CONCLUSION

Even after controlling the possible biophysical and geographical variables, the study reveals that the health program initiatives have a major role to play in reducing under-five mortality rate in the high focus states in India.

National and regional associations between human West Nile virus incidence and demographic, landscape, and land use conditions in the coterminous United States

The incidence of human West Nile virus (WNV) varies spatially and temporally and is influenced by a wide range of biotic and abiotic factors. There are numerous important vector species, with variable geographic ranges and ecologies, considered crucial to the transmission of WNV in the coterminous United States. To date there has been a lack of a systematic investigation in the United States, at a regional scale, of the wide variety of landscape, land use, and demographic influences on WNV incidence. In this study, we use published vector species distribution maps, as well as prominent landscape features, to define six distinct regions of the coterminous United States. We relate data on demographic, landscape, and land use conditions to the incidence of human WNV by region recorded at county level in the coterminous United States from 2002-2009. The observed relationships varied by region with the Great Plains, Northwest, and Southwest regions showing high WNV incidence associated with rural irrigated landscapes, indicating the importance of Culex tarsalis as the primary vector. In the Southeast, the percent of the population in poverty was positively associated with high WNV incidence, potentially indicating the quality of housing in relation to the vector Culex quinquefasciatus, a mosquito that often feeds indoors. The Northeast region human WNV incidence was positively associated with agricultural landscapes, potentially implying the importance of Culex restuans in a region generally thought of as being dominated by Culex pipiens transmission. There was strong spatial autocorrelation in most of the regions, but with a spatial autologistic term accounted for in binary logistic regression models, there were significant landscape, land use, and demographic covariates for each region.

Analysing spatio-temporal clustering of meningococcal meningitis outbreaks in Niger reveals opportunities for improved disease control

BACKGROUND

Meningococcal meningitis is a major health problem in the "African Meningitis Belt" where recurrent epidemics occur during the hot, dry season. In Niger, a central country belonging to the Meningitis Belt, reported meningitis cases varied between 1,000 and 13,000 from 2003 to 2009, with a case-fatality rate of 5-15%.

METHODOLOGY/PRINCIPAL FINDINGS

In order to gain insight in the epidemiology of meningococcal meningitis in Niger and to improve control strategies, the emergence of the epidemics and their diffusion patterns at a fine spatial scale have been investigated. A statistical analysis of the spatio-temporal distribution of confirmed meningococcal meningitis cases was performed between 2002 and 2009, based on health centre catchment areas (HCCAs) as spatial units. Anselin's local Moran's I test for spatial autocorrelation and Kulldorff's spatial scan statistic were used to identify spatial and spatio-temporal clusters of cases. Spatial clusters were detected every year and most frequently occurred within nine southern districts. Clusters most often encompassed few HCCAs within a district, without expanding to the entire district. Besides, strong intra-district heterogeneity and inter-annual variability in the spatio-temporal epidemic patterns were observed. To further investigate the benefit of using a finer spatial scale for surveillance and disease control, we compared timeliness of epidemic detection at the HCCA level versus district level and showed that a decision based on threshold estimated at the HCCA level may lead to earlier detection of outbreaks.

CONCLUSIONS/SIGNIFICANCE

Our findings provide an evidence-based approach to improve control of meningitis in sub-Saharan Africa. First, they can assist public health authorities in Niger to better adjust allocation of resources (antibiotics, rapid diagnostic tests and medical staff). Then, this spatio-temporal analysis showed that surveillance at a finer spatial scale (HCCA) would be more efficient for public health response: outbreaks would be detected earlier and reactive vaccination would be better targeted.

Spatially explicit analyses of anopheline mosquitoes indoor resting density: implications for malaria control

Background

The question of sampling and spatial aggregation of malaria vectors is central to vector control efforts and estimates of transmission. Spatial patterns of anopheline populations are complex because mosquitoes' habitats and behaviors are strongly heterogeneous. Analyses of spatially referenced counts provide a powerful approach to delineate complex distribution patterns, and contributions of these methods in the study and control of malaria vectors must be carefully evaluated.

Methodology/Principal Findings

We used correlograms, directional variograms, Local Indicators of Spatial Association (LISA) and the Spatial Analysis by Distance IndicEs (SADIE) to examine spatial patterns of Indoor Resting Densities (IRD) in two dominant malaria vectors sampled with a 5×5 km grid over a 2500 km² area in the forest domain of Cameroon. SADIE analyses revealed that the distribution of Anopheles gambiae was different from regular or random, whereas there was no evidence of spatial pattern in Anopheles funestus (Ia = 1.644, Pa<0.05 and Ia = 1.464, Pa>0.05, respectively). Correlograms and variograms showed significant spatial autocorrelations at small distance lags, and indicated the presence of large clusters of similar values of abundance in An. gambiae while An. funestus was characterized by smaller clusters. The examination of spatial patterns at a finer spatial scale with SADIE and LISA identified several patches of higher than average IRD (hot spots) and clusters of lower than average IRD (cold spots) for the two species. Significant changes occurred in the overall spatial pattern, spatial trends and clusters when IRDs were aggregated at the house level rather than the locality level. All spatial analyses unveiled scale-dependent patterns that could not be identified by traditional aggregation indices.

Conclusions/Significance

Our study illustrates the importance of spatial analyses in unraveling the complex spatial patterns of malaria vectors, and highlights the potential contributions of these methods in malaria control.

The role of hydrogeography and climate in the landscape epidemiology of West Nile virus in New York State from 2000 to 2010

The epidemiology and ecology of West Nile virus (WNV) have not yet been completely described. In particular, the specific roles of climate and water in the landscape in the occurrence of human WNV cases remain unknown. This study used Poisson regression to describe the relationships between WNV cases and temperature, precipitation, and the hydrogeography of the landscape in New York State from 2000 to 2010. Fully adjusted models showed that hydrogeographic area was significantly inversely associated with WNV cases (incidence rate ratio (IRR) = 0.99; 95% C.I. = 0.98-0.997, p = 0.04), such that each one square kilometer increase in hydrogeographic area was associated with a 1% decrease in WNV incidence. This association was independent of both temperature, which was also associated with WNV incidence (IRR = 2.06; 95% C.I. = 1.84-2.31, p<0.001), and precipitation, which was not (IRR = 1.0; 95% C.I. = 0.99-1.01, p = 0.16). While the results are only suggestive due to the county-level aggregated data, these findings do identify a potentially important surveillance signal in the landscape epidemiology of WNV infection.

Comparing spatio-temporal clusters of arthropod-borne infections using administrative medical claims and state reported surveillance data

Considered separately, notifiable disease registries and medical claims data have certain advantages (e.g., consistent case definitions and electronic records, respectively) and limitations (e.g., incomplete reporting and coding errors, respectively) within disease outbreak research. Combined however, these data could provide a more complete source of information. Using a retrospective space-time permutation scan statistic, zoonotic case information from a state registry system (TDH) was compared with administrative medical claims information from a managed care organization (MCO) to examine how data sources differ. Study observations included case information for four tick-borne (Lyme disease, ehrlichiosis, Rocky Mountain spotted fever, tularemia) and two mosquito-borne diseases (West Nile virus, La Crosse viral encephalitis) occurring in Tennessee. One hundred and three clusters were detected, of which nine were significant (P<0.05). Considering only significant clusters, no spatial or temporal overlapping between data sources occurred. In conclusion, data integration efforts and data limitations should be considered to provide more comprehensive case information.

Yard flooding by irrigation canals increased the risk of West Nile disease in El Paso, Texas

PURPOSE

To investigate the effects of use of water from irrigation canals to flood residential yards on the risk of West Nile disease in El Paso, Texas.

METHODS

West Nile disease confirmed cases in 2009 through 2010 were compared with a random sample of 50 residents of the county according to access to and use of water from irrigation canals by subjects or their neighbors, as well as geo-referenced closest distance between their home address and the nearest irrigation canal. A windshield survey of 600 m around the study subjects' home address recorded the presence of irrigation canals. The distance from the residence of 182 confirmed cases of West Nile disease reported in 2003 through 2010 to canals was compared with that of the centroids of 182 blocks selected at random.

RESULTS

Cases were more likely than controls to report their neighbors flooded their yards with water from canals. Irrigation canals were more often observed in neighborhoods of cases than of controls. Using the set of addresses of 182 confirmed cases and 182 hypothetical controls the authors found a significant, inverse relation with risk of West Nile disease.

CONCLUSIONS

Flooding of yards with water from canals increased the risk of West Nile disease.

Temporal Variations in the Distribution of West Nile Virus Within the United States; 2000-2008

West Nile Virus (WNV) is a serious illness that has affected thousands of people in the United States. Over 1,000 disease related deaths have occurred since its introduction to American soil in 1999. Spatial statistics are used to analyze distributional trends of human WNV cases from 2000 to 2008 through four analyses: Weighted Mean Center, Standard Deviational Ellipses, Global Moran's I, and Getis-Ord-Gi* statistic (hot spot analysis). We conclude that the directional trend in cases has been from East to West with the area affected increasing with time. Hot spot analysis reveals that recurring counties with a high number of human cases have been in the metro areas of large cities. However, normalized results indicate that the rate of humans showing symptoms of WNV is greatest in rural areas, particularly the Great Plains. These results provide a foundation for future research in analyzing the most persistent hot spots in more detail. Furthermore, these findings may aid decision makers in identifying areas to target for mitigation strategies such as spraying, larval control, and public awareness.

A spatial epidemiological analysis of self-rated mental health in the slums of Dhaka

BACKGROUND

The deprived physical environments present in slums are well-known to have adverse health effects on their residents. However, little is known about the health effects of the social environments in slums. Moreover, neighbourhood quantitative spatial analyses of the mental health status of slum residents are still rare. The aim of this paper is to study self-rated mental health data in several slums of Dhaka, Bangladesh, by accounting for neighbourhood social and physical associations using spatial statistics. We hypothesised that mental health would show a significant spatial pattern in different population groups, and that the spatial patterns would relate to spatially-correlated health-determining factors (HDF).

METHODS

We applied a spatial epidemiological approach, including non-spatial ANOVA/ANCOVA, as well as global and local univariate and bivariate Moran's I statistics. The WHO-5 Well-being Index was used as a measure of self-rated mental health.

RESULTS

We found that poor mental health (WHO-5 scores < 13) among the adult population (age ≥15) was prevalent in all slum settlements. We detected spatially autocorrelated WHO-5 scores (i.e., spatial clusters of poor and good mental health among different population groups). Further, we detected spatial associations between mental health and housing quality, sanitation, income generation, environmental health knowledge, education, age, gender, flood non-affectedness, and selected properties of the natural environment.

CONCLUSIONS

Spatial patterns of mental health were detected and could be partly explained by spatially correlated HDF. We thereby showed that the socio-physical neighbourhood was significantly associated with health status, i.e., mental health at one location was spatially dependent on the mental health and HDF prevalent at neighbouring locations. Furthermore, the spatial patterns point to severe health disparities both within and between the slums. In addition to examining health outcomes, the methodology used here is also applicable to residuals of regression models, such as helping to avoid violating the assumption of data independence that underlies many statistical approaches. We assume that similar spatial structures can be found in other studies focussing on neighbourhood effects on health, and therefore argue for a more widespread incorporation of spatial statistics in epidemiological studies.

Space–time pattern of hepatitis A in Spain, 1997–2007

In Spain hepatitis A is a compulsory notifiable disease and individual cases are reported to the national epidemiological surveillance network. Incidence rates show variations in different regions. The aim of this study was to analyse the space–time pattern of hepatitis A risk at municipal level in Spain and at global and local levels during the period 1997–2007. At global level we used two estimates of risk: the standardized incidence ratio (SIR) and the posterior probability that the smoothed relative risk is >1 (PP). At local level we used the scan statistic method to analyse the space–time clusters. The SIR and significant PP (>0·8) showed the highest risk concentrated in areas of the Mediterranean coast. The most likely cluster gave a relative risk of 53·530. These spatial statistics methodologies can be complementary tools in the epidemiological surveillance of infectious diseases.