Space-time clusters and co-occurrence of Plasmodium vivax and Plasmodium falciparum malaria in West Bengal, India.

BACKGROUND: Malaria, a prominent vector borne disease causing over a million annual cases worldwide, predominantly affects vulnerable populations in the least developed regions. Despite their preventable and treatable nature, malaria remains a global public health concern. In the last decade, India has faced a significant decline in malaria morbidity and mortality. As India pledged to eliminate malaria by 2030, this study examined a decade of surveillance data to uncover space-time clustering and seasonal trends of Plasmodium vivax and Plasmodium falciparum malaria cases in West Bengal. METHODS: Seasonal and trend decomposition using Loess (STL) was applied to detect seasonal trend and anomaly of the time series. Univariate and multivariate space-time cluster analysis of both malaria cases were performed at block level using Kulldorff's space-time scan statistics from April 2011 to March 2021 to detect statistically significant space-time clusters. RESULTS: From the time series decomposition, a clear seasonal pattern is visible for both malaria cases. Statistical analysis indicated considerable high-risk P. vivax clusters, particularly in the northern, central, and lower Gangetic areas. Whereas, P. falciparum was concentrated in the western region with a significant recent transmission towards the lower Gangetic plain. From the multivariate space-time scan statistics, the co-occurrence of both cases were detected with four significant clusters, which signifies the regions experiencing a greater burden of malaria cases. CONCLUSIONS: Seasonal trends from the time series decomposition analysis show a gradual decline for both P. vivax and P. falciparum cases in West Bengal. The space-time scan statistics identified high-risk blocks for P. vivax and P. falciparum malaria and its co-occurrence. Both malaria types exhibit significant spatiotemporal variations over the study area. Identifying emerging high-risk areas of P. falciparum malaria over the Gangetic belt indicates the need for more research for its spatial shifting. Addressing the drivers of malaria transmission in these diverse clusters demands regional cooperation and strategic strategies, crucial steps towards overcoming the final obstacles in malaria eradication.

Severe weather events and cryptosporidiosis in Aotearoa New Zealand: A case series of space-time clusters.

Occurrence of cryptosporidiosis has been associated with weather conditions in many settings internationally. We explored statistical clusters of human cryptosporidiosis and their relationship with severe weather events in New Zealand (NZ). Notified cases of cryptosporidiosis from 1997 to 2015 were obtained from the national surveillance system. Retrospective space-time permutation was used to identify statistical clusters. Cluster data were compared to severe weather events in a national database. SaTScan analysis detected 38 statistically significant cryptosporidiosis clusters. Around a third (34.2%, 13/38) of these clusters showed temporal and spatial alignment with severe weather events. Of these, nearly half (46.2%, 6/13) occurred in the spring. Only five (38%, 5/13) of these clusters corresponded to a previously reported cryptosporidiosis outbreak. This study provides additional evidence that severe weather events may contribute to the development of some cryptosporidiosis clusters. Further research on this association is needed as rainfall intensity is projected to rise in NZ due to climate change. The findings also provide further arguments for upgrading the quality of drinking water sources to minimize contamination with pathogens from runoff from livestock agriculture.

Fine-scale spatial clustering of measles nonvaccination that increases outbreak potential is obscured by aggregated reporting data.

The United States experienced historically high numbers of measles cases in 2019, despite achieving national measles vaccination rates above the World Health Organization recommendation of 95% coverage with two doses. Since the COVID-19 pandemic began, resulting in suspension of many clinical preventive services, pediatric vaccination rates in the United States have fallen precipitously, dramatically increasing risk of measles resurgence. Previous research has shown that measles outbreaks in high-coverage contexts are driven by spatial clustering of nonvaccination, which decreases local immunity below the herd immunity threshold. However, little is known about how to best conduct surveillance and target interventions to detect and address these high-risk areas, and most vaccination data are reported at the state-level-a resolution too coarse to detect community-level clustering of nonvaccination characteristic of recent outbreaks. In this paper, we perform a series of computational experiments to assess the impact of clustered nonvaccination on outbreak potential and magnitude of bias in predicting disease risk posed by measuring vaccination rates at coarse spatial scales. We find that, when nonvaccination is locally clustered, reporting aggregate data at the state- or county-level can result in substantial underestimates of outbreak risk. The COVID-19 pandemic has shone a bright light on the weaknesses in US infectious disease surveillance and a broader gap in our understanding of how to best use detailed spatial data to interrupt and control infectious disease transmission. Our research clearly outlines that finer-scale vaccination data should be collected to prevent a return to endemic measles transmission in the United States.

Spatiotemporal and seasonality analysis of sheep and goat pox (SGP) disease outbreaks in Turkey between 2010 and 2019.

Sheep and goat pox (SGP) is a highly infectious disease with a high case fatality rate. It causes serious economic losses and decreases productivity in infected facilities and contact areas. As in many countries of the world, SGP outbreaks reported from Turkey to the World Organization for Animal Health (OIE) continue to threaten animal health. Therefore, studies that will guide the production of effective policies to prevent and control SGP are extremely important. This study aims at evaluating the spatiotemporal distribution of SGP outbreaks by geographical information system (GIS)-based analyses. In accordance with this purpose, spatiotemporal scan analyses were applied to reveal the spatiotemporal distribution pattern and transmission of SGP outbreaks reported in Turkey between 2010 and 2019. Space-time cluster analysis revealed 4 several clusters, indicating geographic areas at the highest risk. Spatiotemporal clusters were 6 to 11 times more likely to be exposed to SGP than the general distribution. The average spatiotemporal density of outbreaks in clusters was estimated as 0.20 ± 0.07 outbreaks per 1000 km2 per month. Seasonal analysis and time series analysis showed similar findings. The seasonality of SGP was mainly defined in the winter (from December to February) when the seasonal adjusted factor (SAF) was at a peak of 504.6. In addition, February had the highest SAF with 7.1. Directional distribution analysis showed that the transmission of SGP was oriented between northeast (NE)-southwest (SW) and northwest (NW)-southeast (SE) and that distribution was changed every 2 years. These findings present a basis for the effective monitoring and prevention of SGP and provide valuable information to policymakers.

Geographical distribution and space-time clustering of human illnesses with major Salmonella serotypes in Florida, USA, 2017-2018.

Nontyphoidal salmonellosis is the leading reported foodborne illness in Florida. Although the diversity of Salmonella serotypes circulating in Florida has been identified, the geographical characteristics of the major serotypes are poorly described. Here we examined the geospatial patterns of 803 whole-genome sequenced Salmonella isolates within seven major serotypes (Enteritidis, Newport, Javiana, Sandiego, Braenderup, Typhimurium and I 4,[5],12:i:-) with the metadata obtained from Florida Department of Health during 2017-2018. Geographically, the distribution of incidence rates varied distinctively between serotypes. Illnesses with Enteritidis and Newport serotypes were widespread in Florida. The incidence rate for Javiana was relatively higher in the north compared to the south. Typhimurium was concentrated in the northwest, while I 4,[5],12:i:-, the monophasic variant of Typhimurium was limited to the south. We also evaluated space-time clustering of isolates at the zip code level using scan statistic models. Space-time clusters were detected for each major serotype during 2017-2018. The multinomial scan statistic found the risk of illness with Javiana was higher in the north and southwest in the fall of 2017 compared to other major serotypes. This serotype-specific clustering analysis will assist in further unpacking the associations between distinct reservoirs and illnesses with major serotypes in Florida.

Preponderance of vaccine-preventable diseases hotspots in northern Ghana: a spatial and space-time clustering analysis from 2010 to 2014.

BACKGROUND: Vaccine-preventable diseases (VPDs) persist globally with a disproportionately high burden in Low and Middle-Income Countries (LMICs). Although this might be partly due to the failure to sustain vaccination coverage above 90% in some WHO regions, a more nuanced understanding of VPD transmission beyond vaccination coverage may unveil other important factors in VPD transmission and control. This study identified VPDs hotspots and explored their relationships with ecology, urbanicity and land-use variations (Artisanal and Small-scale Gold Mining (ASGM) activities) in Ghana. METHODS: District-level disease count data from 2010 to 2014 from the Ghana Health Service (GHS) and population data from the Ghana Population and Housing Census (PHC) were used to determine clustering patterns of six VPDs (Measles, Meningitis, Mumps, Otitis media, Pneumonia and Tetanus). Spatial and space-time cluster analyses were implemented in SaTScan using the discrete Poisson model. P-values were estimated using a combination of sequential Monte Carlo, standard Monte Carlo, and Gumbel approximations. RESULTS: The study found a preponderance for VPD hotspots in the northern parts of Ghana and northernmost ecological zones (Sudan Savannah and Guinea Savannah). Incidence of meningitis was higher in the Sudan Savannah ecological zone relative to: Tropical Rain Forest (p = 0.001); Semi Deciduous Forest (p < 0.0001); Transitional Zone (p < 0.0001); Coastal Savannah (p < 0.0001) and Guinea Savannah (p = 0.033). Except for mumps, which recorded a higher incidence in urban districts (p = 0.045), incidence of the other five VPDs did not differ across the urban-rural divide. Whereas spatial analysis suggested that some VPD hotspots (tetanus and otitis media) occur more frequently in mining districts in the southern part of the country, a Mann-Whitney U test revealed a higher incidence of meningitis in non-mining districts (p = 0.019). Pneumonia and meningitis recorded the highest (722.8 per 100,000) and least (0.8 per 100,000) incidence rates respectively during the study period. CONCLUSION: This study shows a preponderance of VPD hotspots in the northern parts of Ghana and in semi-arid ecoclimates. The relationship between ASGM activities and VPD transmission in Ghana remains blurred and requires further studies with better spatial resolution to clarify.

Spatial-temporal clustering of malaria using routinely collected health facility data on the Kenyan Coast.

BACKGROUND: The over-distributed pattern of malaria transmission has led to attempts to define malaria "hotspots" that could be targeted for purposes of malaria control in Africa. However, few studies have investigated the use of routine health facility data in the more stable, endemic areas of Africa as a low-cost strategy to identify hotspots. Here the objective was to explore the spatial and temporal dynamics of fever positive rapid diagnostic test (RDT) malaria cases routinely collected along the Kenyan Coast. METHODS: Data on fever positive RDT cases between March 2018 and February 2019 were obtained from patients presenting to six out-patients health-facilities in a rural area of Kilifi County on the Kenyan Coast. To quantify spatial clustering, homestead level geocoded addresses were used as well as aggregated homesteads level data at enumeration zone. Data were sub-divided into quarterly intervals. Kulldorff's spatial scan statistics using Bernoulli probability model was used to detect hotspots of fever positive RDTs across all ages, where cases were febrile individuals with a positive test and controls were individuals with a negative test. RESULTS: Across 12 months of surveillance, there were nine significant clusters that were identified using the spatial scan statistics among RDT positive fevers. These clusters included 52% of all fever positive RDT cases detected in 29% of the geocoded homesteads in the study area. When the resolution of the data was aggregated at enumeration zone (village) level the hotspots identified were located in the same areas. Only two of the nine hotspots were temporally stable accounting for 2.7% of the homesteads and included 10.8% of all fever positive RDT cases detected. CONCLUSION: Taking together the temporal instability of spatial hotspots and the relatively modest fraction of the malaria cases that they account for; it would seem inadvisable to re-design the sub-county control strategies around targeting hotspots.

Space-time clustering and temporal trends of hospitalizations due to pulmonary tuberculosis: potential strategy for assessing health care policies.

BACKGROUND: Tuberculosis (TB) causes pressure on healthcare resources, especially in terms of hospital admissions, despite being considered an ambulatory care-sensitive condition for which timely and effective care in ambulatory setting could prevent the need for hospitalization. Our objectives were to describe the spatial and temporal variation in pulmonary tuberculosis (PTB) hospitalizations, identify critical geographic areas at municipality level and characterize clusters of PTB hospitalizations to help the development of tailored disease management strategies that could improve TB control. METHODS: Ecologic study using sociodemographic, geographical and clinical information of PTB hospitalization cases from continental Portuguese public hospitals, between 2002 and 2016. Descriptive statistics, spatiotemporal cluster analysis and temporal trends were conducted. RESULTS: The space-time analysis identified five clusters of higher rates of PTB hospitalizations (2002-16), including the two major cities in the country (Lisboa and Porto). Globally, we observed a -7.2% mean annual percentage change in rate with only one of the identified clusters (out of six) with a positive trend (+4.34%). In the more recent period (2011-16) was obtained a mean annual percentage change in rate of -8.12% with only one cluster identified with an increase trend (+9.53%). CONCLUSIONS: Our results show that space-time clustering and temporal trends analysis can be an invaluable resource to monitor the dynamic of the disease and contribute to the design of more effective, focused interventions. Interventions such as enhancing the detection of active and latent infection, improving monitoring and evaluation of treatment outcomes or adjusting the network of healthcare providers should be tailored to the specific needs of the critical areas identified.

Spatio-temporal trend of BIRADS classification suggestive of malignancy: a national analysis of mammograms, 2013-2017.

INTRODUCTION: Promoting breast cancer (BC) detection in women by means of mammography is a viable strategy to reduce the number of diagnoses at clinically advanced stages and mortality. OBJECTIVES: To describe the results reported by mammography studies in women, carried out nationally during 2013-2017, and to analyze the spatiotemporal trend of Breast Imaging Reporting and Data System (BIRADS) categories suggestive of malignancy by State. METHOD: Longitudinal, analytical design that included information on mammography studies of women according to age group (< 40 and ≥ 40), evaluated in units of the Ministry of Health of Mexico during 2013-2017. The frequency of BIRADS categories and a standardized rate suggestive of malignancy (categories 4 and 5) were estimated in women aged ≥ 40 years, and spatial statistics were used to analyze the trend by State. RESULTS: A total of 3,659,151 mammograms were analyzed, 98.5 % in women aged ≥ 40 years. The malignancy-suggestive rate decreased from 38.3 (2013) to 31 (2017) per 100,000 women aged ≥ 40 years; however, the risk of detection increased up to 13 times in ten States. CONCLUSIONS: Although the risk of detection in categories suggestive of malignancy decreased at the national level, some States need to reinforce the application of BC detection programs through mammography and increase the participation of the target population.

INTRODUCCIÓN: Promover la detección de cáncer de mama (CaMa) en mujeres mediante mastografía es una estrategia viable para disminuir los diagnósticos en fases clínicamente avanzadas y la mortalidad. OBJETIVOS: Describir los resultados reportados por estudios de mastografía en mujeres realizados a nivel nacional durante 2013-2017 y analizar la tendencia espaciotemporal de categorías BIRADS (Breast Imaging Reporting and Data System) sugestivas de malignidad por Estado. MÉTODO: Diseño analítico longitudinal que incluyó información sobre estudios de mastografía de mujeres según grupo de edad (< 40 e ≥ 40), valoradas en unidades de la Secretaría de Salud, México, durante 2013-2017. Se estimó la frecuencia de categorías según BIRADS, tasa estandarizada sugestiva de malignidad (categorías 4 y 5) en mujeres ≥ 40 años y se utilizó estadística espacial para analizar la tendencia por Estado. RESULTADOS: Se analizaron 3,659,151 mastografías, el 98.5 % en mujeres ≥ 40 años. La tasa sugestiva de malignidad disminuyó de 38.3 (2013) a 31 (2017) por 100 mil mujeres ≥ 40 años; sin embargo, el riesgo de detección aumentó hasta 13 veces en diez Estados. CONCLUSIONES: Aunque el riesgo de detección en categorías sugestivas de malignidad disminuyó a nivel nacional, algunos Estados requieren reforzar la aplicación de programas de detección del CaMa mediante mastografía e incrementar la participación de la población blanco.

ClustR: A Space-Time Cluster Analysis R Package for Individual-level Data.

BACKGROUND: Until recently, large individual-level longitudinal data were unavailable to investigate clusters of disease, driving a need for suitable statistical tools. We introduce a robust, efficient, intuitive R package, ClustR, for space-time cluster analysis of individual-level data. METHODS: We developed ClustR and evaluated the tool using a simulated dataset mirroring the population of California with constructed clusters. We assessed Cluster's performance under various conditions and compared it with another space-time clustering algorithm: SaTScan. RESULTS: ClustR mostly exhibited high sensitivity for urban clusters and low sensitivity for rural clusters. Specificity was generally high. Compared with SaTScan, ClustR ran faster and demonstrated similar sensitivity, but had lower specificity. Select cluster types were detected better by ClustR than SaTScan and vice versa. CONCLUSION: ClustR is a user-friendly, publicly available tool designed to perform efficient cluster analysis on individual-level data, filling a gap among current tools. ClustR and SaTScan exhibited different strengths and may be useful in conjunction.

Spatial-Temporal Cluster Analysis of Childhood Cancer in California.

BACKGROUND: The observance of nonrandom space-time groupings of childhood cancer has been a concern of health professionals and the general public for decades. Many childhood cancers are suspected to have initiated in utero; therefore, we examined the spatial-temporal randomness of the birthplace of children who later developed cancer. METHODS: We performed a space-time cluster analysis using birth addresses of 5,896 cases and 23,369 population-based, age-, sex-, and race/ethnicity-matched controls in California from 1997 to 2007, evaluating 20 types of childhood cancer and three a priori designated subgroups of childhood acute lymphoblastic leukemia (ALL). We analyzed data using a newly designed semiparametric analysis program, ClustR, and a common algorithm, SaTScan. RESULTS: We observed evidence for nonrandom space-time clustering for ALL diagnosed at 2-6 years of age in the South San Francisco Bay Area (ClustR P = 0.04, SaTScan P = 0.07), and malignant gonadal germ cell tumors in a region of Los Angeles (ClustR P = 0.03, SaTScan P = 0.06). ClustR did not identify evidence of clustering for other childhood cancers, although SaTScan suggested some clustering for Hodgkin lymphoma (P = 0.09), astrocytoma (P = 0.06), and retinoblastoma (P = 0.06). CONCLUSIONS: Our study provides evidence that childhood ALL diagnosed at 2-6 years and malignant gonadal germ cell tumors sporadically occurs in nonrandom space-time clusters. Further research is warranted to identify epidemiologic features that may inform the underlying etiology.

Space-time clustering of childhood leukemia in Colombia: a nationwide study.

BACKGROUND: Leukemia is the most common cancer in childhood. The estimated incidence rate of childhood leukemia in Colombia is one of the highest in America and little is known about its spatial distribution. PURPOSE: To explore the presence of space-time clustering of childhood leukemia in Colombia. METHODS: We included children less than 15 years of age with confirmed diagnosis of acute leukemia reported to the national surveillance system for cancer between 2009 and 2017. Kulldorff's spatio-temporal scan statistics were used with municipality and year of diagnosis as units for spatial and temporal analysis. RESULTS: There were 3846 cases of childhood leukemia between 2009 and 2017 with a specific mean incidence rate of 33 cases per million person-years in children aged 0-14 years. We identified five spatial clusters of childhood leukemia in different regions of the country and specific time clustering during the study period. CONCLUSION: Childhood leukemia seems to cluster in space and time in some regions of Colombia suggesting a common etiologic factor or conditions to be studied.

Premature mortality of gastrointestinal cancer in Iran: trends and projections 2001-2030.

BACKGROUND: The present study was conducted to determine the trend and projection of premature mortality from gastrointestinal cancers (GI cancers) at national and subnational levels in Iran. METHODS: Employing the data obtained from Iranian Death Registry System (DRS) and population data from census, the mortality rates of GI cancers was calculated among 30-70 age groups. The trends of esophageal, colon and rectum, gallbladder, pancreases, stomach, and liver cancer premature mortalities were estimated and projected at the national and subnational levels from 2001 to 2030. Then, Spatio-temporal model was used to project spatial and temporal correlations. RESULTS: The overall mortality rate of GI cancers was higher in males than in females, indicating 6.1, 3.9 and 3.9% per 100,000 individuals among males in 2001, 2015 and 2030 respectively and 3.8, 3.1 and 3.7 per 100,000 individuals among females in the same time-frame. The overall mortality rate of GI cancers in males was decreasing until 2015 and will remain stationary into 2030; however, the rate will be increasing among females in both time-frames. Also, there was a considerable variation in the mortality trends of different cancers. Pancreatic, gallbladder, and liver cancers were shown to have an increasing trend while a drop was observed in the mortality rates of stomach, colon and rectum, and esophageal cancers. CONCLUSION: Variation of GI cancers patterns and trends around the country indicated that a more comprehensive control plan is needed to include the predicted variations.

Overview of acute diarrheal disease at the dawn of the 21st century: The case of Mexico.

OBJECTIVE: To provide an overview of morbidity and mortality due to acute diarrheal disease in Mexico in order to understand its magnitude, distribution, and evolution from 2000 to 2016. MATERIALS AND METHODS: We carried out a longitudinal ecological study with secondary sources of information. We used data from epidemiological surveillance, health services, and vital statistics. We calculated and mapped measures of utilization of health services rates and mortality due to diarrheal diseases. RESULTS: Diarrhea morbidity decreased by 42.1% across the period. However, emergency department attendances increased by 50.7% in the Ministry of Health. The hospitalization rate and mortality among the general population decreased by 37.6 and 39.7%, respectively, and the infant mortality rate decreased by 72.3% among children under five years of age. Chiapas and Oaxaca had the highest mortality among the states of Mexico. CONCLUSIONS: Cases of diarrhea, including rotavirus, have decreased in Mexico. However, in 2016, 3.4 per 100 000 people died due to diarrhea, which could have been avoided with health promotion.

OBJETIVO: Ofrecer un panorama de la morbimortalidad por enfermedad diarreica aguda (EDA) entre 2000 y 2016 en México, para entender su magnitud, distribución y evolución. MATERIAL Y MÉTODOS: Estudio ecológico longitudinal, con fuentes de información secundarias. Se analizaron datos de vigilancia epidemiológica, prestación de servicios y estadísticas vitales. Se calcularon tasas de utilización de servicios y mortalidad. RESULTADOS: La morbilidad por EDA disminuyó 42.1% en el periodo, sin embargo, la atención por urgencias aumentó 50.7% en SS. La tasa de hospitalización descendió 37.6% y la mortalidad 39.7% en población general y 72.3% en menores de cinco años. Chiapas y Oaxaca fueron los estados con mayor tasa de mortalidad. CONCLUSIONES: Los casos de diarrea, incluyendo los de rotavirus, han disminuido en el país. Sin embargo, en 2016 se encontró una tasa de 3.4 por 100 000 personas que mueren por EDA, lo cual podría evitarse con promoción de la salud.

Space-time clustering of childhood cancers: a systematic review and pooled analysis.

The aetiology of childhood cancers remains largely unknown. Space-time clustering of cases might imply an aetiological role of infections. We aimed to review the evidence of space-time clustering of specific childhood cancers. We searched Medline and Embase for population-based studies that covered a pre-defined study area, included cases under 20 years of age and were published before July 2016. We extracted all space-time clustering tests and calculated the proportion of positive tests per diagnostic group. In a pooled analysis, we performed a Knox test of the number of pairs of cases close to each other in time and space pooled across studies. 70 studies met our eligibility criteria, 32 of which reported Knox tests. For leukaemia, the proportion of positive tests was higher than expected by chance at both time of diagnosis (26%) and birth (11%). The pooled analysis showed strong evidence of clustering at diagnosis for children aged 0-5 years for a spatial and temporal lag of 5 km and 6 months, respectively (p < 0.001). The evidence was mixed for lymphoma and tumours of the central nervous system. The current study suggests that leukaemia cases cluster in space-time due to an aetiological factor affecting children under 5 years of age. The observed pattern of clustering of young children close to time of diagnosis is compatible with Greaves' delayed-infections-hypothesis.

Factors associated with Legionnaires' disease recurrence in hotel and holiday rental accommodation sites.

BackgroundThe detection of a cluster of travel-associated Legionnaires' disease (TALD) cases in any European Union/European Economic Area (EU/EEA) country prompts action at the accommodation, follow-up by health authorities and reporting of measures taken. Some accommodations incur further cases despite presumed implementation of adequate control measures.AimTo identify factors associated with the occurrence of a further TALD case after the implementation of control measures.MethodsWe conducted a retrospective cohort study of hotel and holiday rental accommodations in the EU/EEA associated with two or more TALD cases with onset dates less than 2 years apart (a 'cluster') and notification between 1 June 2011-31 December 2016. We fitted Cox regression models to estimate the association between accommodation characteristics and the occurrence of a further case, defined as any case with onset date after the report on measures taken.ResultsOf the 357 accommodations in the analysis, 90 (25%) were associated with at least one further case after the report on measures taken (12.4/100 accommodation-years). Accommodations associated with two or more cases before the cluster notification were more likely to be associated with a further case, compared with those not previously associated with any case (adjusted hazard ratio 1.85; 95% confidence interval: 1.14-3.02). Neither the detection of Legionella in the water system nor the type of disinfection were found to be associated with the risk of a further case.ConclusionAccommodation size and previous TALD cases were predictive of further Legionnaires' disease cases after implementation of control measures.

Analysis of domestic animal movements in Colombia (2006-2014) and their possible influence on the bovine brucellosis spread.

Bovine brucellosis is a zoonotic disease that causes great economic losses. The disease is endemic in Colombia and animal movements from infected herds carry a risk of introduction to other herds. With the objective of analyzing the animal movements and determining their relationship with bovine brucellosis, we performed a descriptive analysis of the space-time movement of livestock in Colombia between 2006 and 2014. Multiple linear regression models (MLR) were employed to determine the relationship between brucellosis status and animal movements at the province level. The prevalence of bovine brucellosis in cattle was the dependent variable, and a total of 14 independent variables related to location, year, census, and animal movements were included. The prevalence of bovine brucellosis was significantly affected by the province (F = 3.42; P < 0.001), the year (F = 9.03; P < 0.001), and bovine (F = 5.45; P = 0.02) and equine movements (F = 3.8; P = 0.053). Fewer cattle and more horses entered provinces with high prevalence than those with low prevalence, indicating the possible relationship between the animal movements and the brucellosis infection in the country.

Spatial clustering of childhood cancers in Switzerland: a nationwide study.

PURPOSE: Childhood cancers are rare and little is known about their etiology. Potential risk factors include environmental exposures that might implicate spatial variation of cancer risk. Previous studies of spatial clustering have mainly focused on childhood leukemia. We investigated spatial clustering of different childhood cancers in Switzerland using exact geocodes of place of residence. METHODS: We included 6,034 cancer cases diagnosed at age 0-15 years during 1985-2015 from the Swiss Childhood Cancer Registry. Age and sex-matched controls (10 per case) were randomly sampled from the national censuses (1990, 2000, 2010). Geocodes of place of residence were available at birth and diagnosis for both cases and controls. We used the difference in k-functions and Cuzick-Edwards test to assess global clustering and Kulldorff's circular scan to detect individual clusters. We also carefully adjusted for multiple testing. RESULTS: After adjusting for multiple testing, we found no evidence of spatial clustering of childhood cancers neither at birth (p = 0.43) nor diagnosis (p = 0.13). Disregarding multiple testing, results of individual tests indicated spatial clustering of all childhood cancers combined (p < 0.01), childhood lymphoma (p = 0.01), due to Hodgkin lymphoma (HL) (p = 0.02) at diagnosis, and embryonal tumors of the central nervous system (CNS) at birth and diagnosis, respectively (p = 0.05 and p = 0.02). CONCLUSIONS: This study provides weak evidence of spatial clustering of childhood cancers. Evidence was strongest for HL and embryonal CNS tumors, adding to the current literature that these cancers cluster in space.

Mapping the Mental Health of Residents After the 2013 Boston Marathon Bombings.

Postdisaster mental health is typically assessed and treated on an individual basis. Ecological assessments, however, can be a more cost-effective means to identify and promote mental health after a disaster. In this study, the spatial patterning of acute stress scores, probable posttraumatic stress disorder (PTSD), and fears and worries among a representative sample of Boston metropolitan area participants (N = 788) was examined using data collected 2-4 weeks to 2 years after the 2013 Boston Marathon bombings. Findings indicate significant clustering of acute stress scores, Moran's I = 0.24, z = 2.91, p = .004; fears and worries, Moran's I = 0.25, z = 2.39, p = .017; and probable PTSD at Wave 2, Moran's I = 0.49, z = 5.16; p < .001, and at Wave 5, Moran's I = 0.26, z = 2.51, p = .012, in the Boston metropolitan area, with high distress clusters found near downtown Boston and the attack site. These results suggest that disaster mental health is not uniformly distributed across space. Instead, patterns emerge to identify persons and neighborhoods at risk for poor mental health outcomes.

Spatial clustering of childhood leukaemia in Switzerland: A nationwide study.

The aetiology of childhood leukaemia remains largely unknown. Several hypotheses involve environmental exposures that could implicate spatial clustering of cases. The evidence from previous clustering studies is inconclusive. Most of them used areal data and thus had limited spatial resolution. We investigated whether childhood leukaemia tends to cluster in space using exact geocodes of place of residence both at the time of birth or diagnosis. We included 1,871 leukaemia cases diagnosed between 1985 and 2015 at age 0-15 years from the Swiss Childhood Cancer Registry. For each case, we randomly sampled 10 age and sex matched controls from national censuses closest in time. We used the difference of k-functions, Cuzick-Edwards' test and Tango's index for point data to assess spatial clustering and Kulldorff's circular scan to detect clusters. We separately investigated acute lymphoid leukaemia (ALL), acute myeloid leukaemia (AML), different age groups at diagnosis (0-4, 5-15 years) and adjusted for multiple testing. After adjusting for multiple testing, we found no evidence of spatial clustering of childhood leukaemia neither around time of birth (p = 0.52) nor diagnosis (p = 0.51). Individual tests indicated spatial clustering for leukaemia diagnosed at age 5-15 years, p k-functions = 0.05 and p Cuzick-Edwards' = 0.04 and a cluster of ALL cases diagnosed at age 0-4 years in a small rural area (p = 0.05). This study provides little evidence of spatial clustering of childhood leukaemia in Switzerland and highlights the importance of accounting for multiple testing in clustering studies.