Spatial Epidemiological Analysis Research Articles

Geographic Determinants and Spatial Epidemiology of Prescription Drug Abuse: A Comprehensive Analysis of Distribution Patterns, Treatment Accessibility and Intervention Strategies

This study examines the complex spatial patterns and geographic variations in prescription drug abuse, analyzing their impact on treatment outcomes and public health interventions. Through comprehensive spatial epidemiological analysis, we investigate how geographic factors influence abuse patterns across urban, suburban, and rural landscapes. The research synthesizes data on healthcare accessibility, socioeconomic conditions, and regional policy frameworks to understand their collective impact on prescription drug misuse. Our findings reveal significant geographic disparities in treatment accessibility, with rural areas facing substantial barriers to addiction services compared to urban centers. Analysis of prescription drug monitoring programs demonstrates varying effectiveness across regions, highlighting the need for spatially-tailored interventions. The study identifies distinct regional profiles of drug misuse, influenced by factors including healthcare infrastructure, cultural norms, and local regulatory environments. Advanced spatial analysis techniques, including geospatial mapping and hotspot analysis, revealed significant correlations between geographic determinants and abuse patterns. Results indicate that proximity to healthcare facilities, pharmaceutical distribution networks, and demographic characteristics contribute to localized risk profiles. The integration of multiple data sources, including prescription records and treatment admissions, provided insights into space-time clustering of abuse patterns. This research emphasizes the importance of developing geographically-informed approaches to combat prescription drug abuse, suggesting that intervention strategies should be tailored to specific regional contexts while addressing broader systemic issues. The findings have significant implications for public health policy, healthcare resource allocation, and the development of targeted prevention strategies.

Summary Analysis of National Surveillance on Kashin-Beck Disease from 1990 to 2023

ObjectiveTo analyze the epidemiological characteristics and epidemic situation of children with Kashin-Beck disease (KBD) in China, and provide the basis for formulating prevention and control measures. MethodsFixed-point monitoring, moving-point monitoring, and full coverage of monitoring were promoted successively from 1990 to 2023. Some children (7–12 years old) underwent clinical and righthand X-ray examinations every year. According to the KBD diagnosis criteria, clinical and X-ray assessments were used to confirm the diagnosis. ResultsIn 1990, the national KBD detectable rate was 21.01%. X-ray detection decreased to below 10% in 2003 and below 5% in 2007. Between 2010 and 2018, the prevalence of KBD in children was less than 0.4%, which fluctuated at a low level, and has decreased to 0% since 2019. Spatial epidemiological analysis indicated a spatial clustering of adult patients prevalence rate in the KBD areas. ConclusionThe evaluation results of the elimination of KBD in China over the last 5 years showed that all villages in the monitored areas have reached the elimination standard. While the adult KBD patients still need for policy consideration and care.

Combining molecular transmission network analysis and spatial epidemiology to reveal HIV-1 transmission pattern among the older people in Nanjing, China

BackgroundIn China, the problem of HIV infection among the older people has become increasingly prominent. This study aimed to analyze the pattern and influencing factors of HIV transmission based on a genomic and spatial epidemiological analysis among this population.MethodsA total of 432 older people who were aged ≥ 50 years, newly diagnosed with HIV-1 between January 2018 and December 2021 and without a history of ART were enrolled. HIV-1 pol gene sequence was obtained by viral RNA extraction and nested PCR. The molecular transmission network was constructed using HIV-TRACE and the spatial distribution analyses were performed in ArcGIS. The multivariate logistic regression analysis was performed to analyze the factors associated with clustering.ResultsA total of 382 sequences were successfully sequenced, of which CRF07_BC (52.3%), CRF01_AE (32.5%), and CRF08_BC (6.8%) were the main HIV-1 strains. A total of 176 sequences entered the molecular network, with a clustering rate of 46.1%. Impressively, the clustering rate among older people infected through commercial heterosexual contact was as high as 61.7% and three female sex workers (FSWs) were observed in the network. The individuals who were aged ≥ 60 years and transmitted the virus by commercial heterosexual contact had a higher clustering rate, while those who were retirees or engaged other occupations and with higher education degree were less likely to cluster. There was a positive spatial correlation of clustering rate (Global Moran I = 0.206, P < 0.001) at the town level and the highly aggregated regions were mainly distributed in rural area. We determined three large clusters which mainly spread in the intra-region of certain towns in rural areas. Notably, 54.5% of cases in large clusters were transmitted through commercial heterosexual contact.ConclusionsOur joint analysis of molecular and spatial epidemiology effectively revealed the spatial aggregation of HIV transmission and highlighted that towns of high aggregation were mainly located in rural area. Also, we found vital role of commercial heterosexual contact in HIV transmission among older people. Therefore, health resources should be directed towards highly aggregated rural areas and prevention strategy should take critical persons as entry points.

Spatial epidemiological analysis of the burden of liver cancer in China.

Liver cancer is one of the most common cancers in the world, with unique regional variations in disability-adjusted life years (DALY) rate, nearly 50% of liver cancer cases occur in China. Therefore, understanding the epidemiological characteristics of liver cancer is of utmost importance. In this study, to analyze the spatial distribution characteristics and clustering of the DALY rate of liver cancer in 1990 and 2017 in China based on provincial administrative divisions, and to explore its possible influencing factor. The DALY rate data of liver cancer at the provincial level in China were collected, the global autocorrelation of the DALY rate was analyzed by Moran's I, the local autocorrelation of the DALY rate was analyzed by Getis-Ord-Gi*, and the influencing factors related to the DALY rate were analyzed by the least squares regression model. The DALY rate of liver cancer in China generally showed an increasing trend. The DALY rate increased in 22 provinces and decreased in nine provinces. In 2017, the distribution of DALY rate in all provinces showed heterogeneity, with the highest DALY rate in Guangxi (1,363.37/100,000) and the lowest in Beijing (315.78/100,000). In 2017, the low and low clustering were mainly concentrated in Inner Mongolia, Ningxia, Shanxi, Hebei, and Tianjin. The low and high clustering in Yunnan, Guizhou, and Guangdong, were surrounded by the high clustering in neighboring provinces, high and high concentration is mainly concentrated in Hunan and neighboring provinces. The results of the least square regression model showed that the per capita years of education, hepatitis B incidence and the proportion of population over 65 years old had an impact on the DALY rate of liver cancer (P<0.05). The DALY rate of liver cancer in China showed an overall increasing trend. In 2017, the DALY rate of liver cancer in China had a spatial aggregation in the whole country, and the per capita years of education, the incidence of hepatitis B and the proportion of population over 65 years old had an impact on the DALY rate of liver cancer in space.

Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging.

To describe the process and epidemiological implications of georeferencing in EpiFloripa Aging samples (2009-2019). The EpiFloripa Aging Cohort Study sought to investigate and monitor the living and health conditions of the older adult population (≥ 60) of Florianópolis in three study waves (2009/2010, 2013/2014, 2017/2019). With an automatic geocoding tool, the residential addresses were spatialized, allowing to investigate the effect of the georeferencing sample losses regarding 19 variables, evaluated in the three waves. The influence of different neighborhood definitions (census tracts, Euclidean buffers, and buffers across the street network) was examined in the results of seven variables: area, income, residential density, mixed land use, connectivity, health unit count, and public open space count. Pearson's correlation coefficients were calculated to evaluate the differences between neighborhood definitions according to three variables: contextual income, residential density, and land use diversity. The losses imposed by geocoding (6%, n = 240) caused no statistically significant difference between the total sample and the geocoded sample. The analysis of the study variables suggests that the geocoding process may have included a higher proportion of participants with better income, education, and living conditions. The correlation coefficients showed little correspondence between measures calculated by the three neighborhood definitions (r = 0.37-0.54). The statistical difference between the variables calculated by buffers and census tracts highlights limitations in their use in the description of geospatial attributes. Despite the challenges related to geocoding, such as inconsistencies in addresses, adequate correction and verification mechanisms provided a high rate of assignment of geographic coordinates, the findings suggest that adopting buffers, favored by geocoding, represents a potential for spatial epidemiological analyses by improving the representation of environmental attributes and the understanding of health outcomes.

What awaits US in the next bird migration in South America: Prospects for the detection and incidence of HPAIV H5N1 in commercial poultry and wild birds. Proceeding of The First International Avian Influenza Summit, University of Arkansas- October 16-17, 2023".

Highly pathogenic avian influenza virus (HPAIV) H5N1 poses a significant threat to both commercial poultry operations and wild bird populations worldwide. South America, with its rich avian biodiversity and extensive poultry industry, is susceptible to the introduction and spread of this devastating virus. This study explores the imminent challenges and potential outcomes associated with the upcoming bird migration season in South America, focusing on the detection and incidence of HPAIV H5N1. Employing a multidisciplinary approach is necessary to integrate spatial modeling, genomic surveillance, and epidemiological analyses to forecast the dynamics of HPAIV H5N1 in the region. By examining historical migration patterns, host susceptibility, and environmental factors, it will be possible to elucidate potential pathways for virus dissemination among wild bird populations and spillover into commercial poultry farms. Furthermore, this study evaluates the efficacy of current surveillance and monitoring strategies in detecting HPAIV H5N1, identifying potential gaps, and offering recommendations for enhanced surveillance protocols. Leveraging advanced molecular techniques is necessary to analyze viral genomes to track potential mutations associated with increased virulence or altered host range, thereby providing crucial insights for targeted intervention measures. The outcomes of this research will advance our understanding of the ecological and epidemiological factors influencing the spread of HPAIV H5N1 in South America and inform proactive strategies for early detection, containment, and mitigation of future outbreaks. This comprehensive assessment is a pivotal step towards safeguarding poultry industries and avian biodiversity in the face of emerging infectious diseases.

Spatial-epidemiological analysis of population aging in counties in Jiangsu Province, 1990-2020

Objective: To analyze the space-time evolution trend of population aging at the county level in Jiangsu Province from 1990 to 2020. Methods: Taking each county of Jiangsu Province as the research object, we selected data from the fourth to the seventh national population censuses. We used the aging coefficient and age concentration rate as static and dynamic indicators to measure the degree of population aging, respectively. We also used spatial correlation analysis to study the spatial and temporal patterns and evolution characteristics of aging in counties in Jiangsu Province. Results: The degree of aging in each county of Jiangsu Province has been deepening, and the degree of aging gradually evolves from high in southern Jiangsu and low in northern Jiangsu to high in central Jiangsu and low in southern and northern Jiangsu and shows obvious spatial aggregation. From 1990 to 2020, the population aging in Jiangsu Province has accelerated, among which the aging from 2010-2020 is the fastest. The aging progress appeares the fastest in 2010-2020. Conclusion: From 1990 to 2020, population aging in Jiangsu Province has been deepening, with the fastest progress in the last decade and an obvious spatial aggregation.

Mapping the risk of respiratory infections using suburban district areas in a large city in Colombia

BackgroundAcute respiratory infections (ARI) in Cúcuta -Colombia, have a comparatively high burden of disease associated with high public health costs. However, little is known about the epidemiology of these diseases in the city and its distribution within suburban areas. This study addresses this gap by estimating and mapping the risk of ARI in Cúcuta and identifying the most relevant risk factors.MethodsA spatial epidemiological analysis was designed to investigate the association of sociodemographic and environmental risk factors with the rate of ambulatory consultations of ARI in urban sections of Cúcuta, 2018. The ARI rate was calculated using a method for spatial estimation of disease rates. A Bayesian spatial model was implemented using the Integrated Nested Laplace Approximation approach and the Besag-York-Mollié specification. The risk of ARI per urban section and the hotspots of higher risk were also estimated and mapped.ResultsA higher risk of IRA was found in central, south, north and west areas of Cúcuta after adjusting for sociodemographic and environmental factors, and taking into consideration the spatial distribution of the city’s urban sections. An increase of one unit in the percentage of population younger than 15 years; the Index of Multidimensional Poverty and the rate of ARI in the migrant population was associated with a 1.08 (1.06—1.1); 1.04 (1.01—1.08) and 1.25 (1.22—1.27) increase of the ARI rate, respectively. Twenty-four urban sections were identified as hotspots of risk in central, south, north and west areas in Cucuta.ConclusionSociodemographic factors and their spatial patterns are determinants of acute respiratory infections in Cúcuta. Bayesian spatial hierarchical models can be used to estimate and map the risk of these infections in suburban areas of large cities in Colombia. The methods of this study can be used globally to identify suburban areas and or specific communities at risk to support the implementation of prevention strategies and decision-making in the public and private health sectors.

Spatial and temporal epidemiological analysis on the mortality rate of female breast cancer in Suzhou, China: 2006–2020

Objective: The epidemiological trend and spatial distribution of female breast cancer mortality in Suzhou were analyzed, so as to provide a scientific basis for the prevention and treatment of breast cancer. Materials and Methods: The annual trend of female breast cancer mortality data from 2006 to 2020 years was analyzed. The spatial autocorrelation analysis was carried out by Moran’s I method of GeoDa software to explore its regional aggregation. Results: The average annual crude mortality rate (CR) of breast cancer in Suzhou was 8.54 per 100 000 from 2006 to 2020, while the age-standardized mortality rate (ASMR) was 7.38 per100 000. The annual change percentage (APC) of CR in the recent 15 years was 1.98% (1.30–2.66%), which was statistically significant (P&lt;0.001). The annual change trend of ASMR was decreased slightly (APC=−0.95%, P=0.04). Spatial analysis indicated that there was a certain clustering of breast cancer in Suzhou. The CR of female breast cancer in Suzhou showed an upward trend, but ASMR decreased slightly. Conclusion: Health promotion and education should be strengthened in the areas with a high incidence of female breast cancer death in Suzhou, and the participation rate of breast cancer screening should be further improved.

The utility of Zip4 codes in spatial epidemiological analysis.

There are many public health situations within the United States that require fine geographical scale data to effectively inform response and intervention strategies. However, a condition for accessing and analyzing such data, especially when multiple institutions are involved, is being able to preserve a degree of spatial privacy and confidentiality. Hospitals and state health departments, who are generally the custodians of these fine-scale health data, are sometimes understandably hesitant to collaborate with each other due to these concerns. This paper looks at the utility and pitfalls of using Zip4 codes, a data layer often included as it is believed to be "safe", as a source for sharing fine-scale spatial health data that enables privacy preservation while maintaining a suitable precision for spatial analysis. While the Zip4 is widely supplied, researchers seldom utilize it. Nor is its spatial characteristics known by data guardians. To address this gap, we use the context of a near-real time spatial response to an emerging health threat to show how the Zip4 aggregation preserves an underlying spatial structure making it potentially suitable dataset for analysis. Our results suggest that based on the density of urbanization, Zip4 centroids are within 150 meters of the real location almost 99% of the time. Spatial analysis experiments performed on these Zip4 data suggest a far more insightful geographic output than if using more commonly used aggregation units such as street lines and census block groups. However, this improvement in analytical output comes at a spatial privy cost as Zip4 centroids have a higher potential of compromising spatial anonymity with 73% of addresses having a spatial k anonymity value less than 5 when compared to other aggregations. We conclude that while offers an exciting opportunity to share data between organizations, researchers and analysts need to be made aware of the potential for serious confidentiality violations.

Time Series and Spatial Epidemiological Analysis of the Prevalence of Iodine Deficiency Disorders in China

ObjectiveTo recognize the spatial and temporal characteristics of iodine deficiency disorders (IDD), China national IDD surveillance data for the years of 1995–2018 were analyzed. MethodsTime series analysis was used to describe and predict the IDD related indicators, and spatial analysis was used to analyze the spatial distribution of salt iodine levels. ResultsIn China, the median urinary iodine concentration increased in 1995–1997, then decreased to adequate levels, and are expected to remain appropriate in 2019–2022. The goiter rate continually decreased and is expected to be maintained at a low level. Since 2002, the coverage rates of iodized salt and the consumption rates of qualified iodized salt (the percentage of qualified iodized salt in all tested salt) increased and began to decline in 2012; they are expected to continue to decrease. Spatial epidemiological analysis indicated a positive spatial correlation in 2016–2018 and revealed feature regarding the spatial distribution of salt related indicators in coastal areas and areas near iodine-excess areas. ConclusionsIodine nutrition in China showed gradual improvements. However, a recent decline has been observed in some areas following changes in the iodized salt supply in China. In the future, more regulations regarding salt management should be issued to strengthen IDD control and prevention measures, and avoid the recurrence of IDD.

Understanding geographic and racial/ethnic disparities in mortality from four major cancers in the state of Georgia: a spatial epidemiologic analysis, 1999–2019

We examined geographic and racial variation in cancer mortality within the state of Georgia, and investigated the correlation between the observed spatial differences and county-level characteristics. We analyzed county-level cancer mortality data collected by the Centers for Disease Control and Prevention on breast, colorectal, lung, and prostate cancer mortality among adults (aged ≥ 18 years) in 159 Georgia counties from years 1999 through 2019. Geospatial methods were applied, and we identified hot spot counties based on cancer mortality rates overall and stratified by non-Hispanic white (NH-white) and NH-black race/ethnicity. Among all adults, 5.0% (8 of 159), 8.2% (13 of 159), 5.0% (8 of 159), and 6.9% (11 of 159) of Georgia counties were estimated hot spots for breast cancer, colorectal, lung, and prostate cancer mortality, respectively. Cancer mortality hot spots were heavily concentrated in three major areas: (1) eastern Piedmont to Coastal Plain regions, (2) southwestern rural Georgia area, or (3) northern-most rural Georgia. Overall, hot spot counties generally had higher proportion of NH-black adults, older adult population, greater poverty, and more rurality. In Georgia, targeted cancer prevention strategies and allocation of health resources are needed in counties with elevated cancer mortality rates, focusing on interventions suitable for NH-black race/ethnicity, low-income, and rural residents.

Abstract 5908: Understanding geographic and racial disparities in mortality from four major cancers in the state of Georgia: A spatial epidemiologic analysis, 1999 - 2019

Abstract Purpose of the study: Progress in cancer outcomes in the general population are not equitable among all populations, leaving some, such as rural and non-Hispanic Blacks (NH-Black) behind. We examined geographic and racial variation in cancer mortality in the state of Georgia, and investigated the correlation between the observed spatial differences and county-level characteristics. Methods: We analyzed data on breast, colorectal, lung, and prostate cancer mortality among adults (aged &amp;gt;18 years) in 159 Georgia counties from years 1999 through 2019. Geospatial methods were applied, and we identified hot spot counties based on cancer mortality rates overall and stratified by non-Hispanic White (NH-White) and NH-Black races. We assessed differences in county-level characteristics between hot spot and non-hot spot counties using Wilcoxon rank-sum test and Spearman correlation and stratified all analyses by race/ethnicity. Results: Among all adults, 5.0% (8 of 159), 8.2% (13 of 159), 5.0% (8 of 159), and 6.9% (11 of 159) of Georgia counties were estimated hot spots for breast cancer, colorectal, lung, and prostate cancer mortality, respectively. Among NH-Whites, 5.7% (9 of 159), 4.4% (7 of 159), 4.4% (7 of 159) counties, and 5.0% (8 of 159) of counties were identified as hot spots for breast, colorectal, lung, and prostate cancer mortality, respectively. Among NH-Blacks, 5.7% (9 of 159), 3.8% (6 of 159), 7.4% (11 of 159), and 5.7% (9 of 159) counties were identified as hot spots for breast, colorectal, lung, prostate cancer mortality, respectively. Cancer mortality hot spots were heavily concentrated in three major areas: 1) eastern Piedmont to Coastal Plain regions, 2) southwestern rural Georgia area, or 3) northern-most rural Georgia. Overall, hot spot counties generally had higher proportion of NH-Blacks, older adult population, greater poverty, and more rurality. Conclusions: We observed distinct geographic and racial/ethnic disparities in mortality from breast, colorectal, lung, and prostate cancer in Georgia. Targeted cancer prevention strategies and allocation of health resources are needed in counties with elevated cancer mortality rates, focusing on interventions suitable for NH-Black, low-income, and rural residents. Citation Format: Justin Xavier Moore, Martha S. Tingen, Steven S. Coughlin, Christine O'Meara, Lorriane Odhiambo, Marlo Vernon, Samantha Jones, Robert Petcu, Ryan Johnson, K.M. Monirul Islam, Darryl Nettles, Ghadeer Albashir, Jorge Cortes. Understanding geographic and racial disparities in mortality from four major cancers in the state of Georgia: A spatial epidemiologic analysis, 1999 - 2019 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5908.

Spatial analysis of echinococcosis in pastoral area of Qinghai province, 2019

Objective: To understand the spatial characteristics of echinococcosis and associated factors in the pastoral area of Qinghai province, and provide evidence for the effective prevention and control of echinococcosis. Methods: The number of echinococcosis cases in the pastoral areas of Qinghai in 2019 was collected to perform spatial epidemiological analysis. The thematic map of the distribution of echinococcosis cases was generated with software ArcGIS 10.8 for visual analysis and spatial autocorrelation analysis. The spatial autocorrelation and spatial scanning analysis were performed to estimate the clustering of echinococcosis with software SaTScan 9.5. Software GeoDa 1.14 and ArcGIS 10.8 were used to establish spatial lag model and geographical weighted regression model to analyze the related factors of echinococcosis epidemic. Results: In 2019, the echinococcosis surveillance covered 64 741 people in the pastoral area of Qinghai, and 829 echinococcosis cases were found, with a prevalence rate of 1.28%. The distribution of the cases had spatial correlation (Moran's I=0.41, P<0.001). The most possible clustering areas indicated by spatial scanning analysis included Banma, Jiuzhi, Dari and Gande counties of Guoluo Tibetan Autonomous Prefecture (LLR=460.77, RR=9.20, P<0.001). The prevalence of echinococcosis in the pastoral areas was positively associated with the total annual precipitation (β=0.13, P=0.036), and negatively associated with population density (β=-1.36, P=0.019) and doctors/nurse ratio (β=-25.60, P=0.026). Conclusions: The distribution of echinococcosis cases in the pastoral areas of Qinghai in 2019 had spatial correlation, and the prevalence was affected by total annual precipitation, population density, and doctors/nurse ratio.

Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020-December 2021.

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020-December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81× faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population.

Spatial epidemiological analysis of Lyme disease in southern Ontario utilizing Google Trends searches

Lyme disease is of growing concern in Ontario with endemic areas increasing in size. Differential diagnosis of Lyme disease patients should include their exposure status assuming knowledge of high-risk areas. The goal of this study was a spatial analysis of Lyme disease in southern Ontario for the years 2015–2019 with a focus on the association between Lyme disease prevalence and Internet search frequencies recorded by Google Trends. A choropleth map visualized the raw prevalence of Lyme disease across the 28 public health units of southern Ontario. A disease cluster comprising five public health units was identified in eastern Ontario using the flexible scan statistic (standard morbidity ratio = 4.9, p = 0.01). Poisson regression modeling revealed an association between Lyme disease prevalence and the search term “Lyme disease” in Google Trends (p = 0.032). Lyme disease prevalence was correlated with Google Trend searches, with an increase in relative risk by a factor of 1.19 (CI95%: 1.03, 1.39) for every 1% increase in search activity. Knowledge of the existence and location of high-risk or exposure areas for Lyme disease is important to properly diagnose patients. Exploiting the association between Lyme disease and Internet search activity by the population at risk can also further disease surveillance.

HIV-1 genetic transmission networks among people living with HIV/AIDS in Sichuan, China: a genomic and spatial epidemiological analysis

SummaryBackgroundSpatialized HIV genetic transmission networks can help understand dynamic changes of HIV-1 at the regional level. This study aimed to combine genomic, epidemiological, and spatial data to investigate the patterns of the HIV-1 epidemic at both individual and regional levels among people living with HIV (PLWH) with virological failure of antiretroviral therapy (ART).MethodsWe evaluated the transmission patterns of 5,790 PLWH with identified pol sequences of the five main HIV-1 subtypes (B, CRF08_BC, CRF85_BC, CRF07_BC, and CRF01_AE) in Sichuan Province, China. A phylogenetic cluster was defined as a group of sequences with genetically similar HIV strains, with all phylogenetic clusters forming an HIV-1 genetic transmission network for each subtype. Logistic regression was used to identify the potential risk factors for phylogenetic clustering. Spatial analysis was applied to demonstrate the geographic patterns of phylogenetic clustering rates; intensity matrices and flow maps were made to demonstrate the intensity of transmission within and between cities.FindingsThere were 2,159 (37.3%) of 5,790 PLWH, distributed in 452 phylogenetic clusters. Some individual clinical and behavioral factors were associated with phylogenetic clustering, including a viral load of >50,000 copies/ml (OR=1.16, 95%CI=1.02-1.33), infection of other sexually transmitted diseases (OR=1.38, 95%CI=1.12-1.69), and ≥5 non-marital sexual partners (OR=1.25, 95%CI=1.03-1.51), while >3 years of treatment since the initial ART was associated with less likelihood of phylogenetic clustering (OR=0.82, 95%CI=0.70-0.97). The phylogenetic clustering rates varied regionally and were highest in the central region of Sichuan, especially for subtype CRF08_BC. The significant spatial clusters of high and low phylogenetic clustering rates were detected in the east (Dazhou for B; Zigong and Luzhou for CFR08_BC) and west (Yaan and Ganzi for CRF07_BC), respectively. The proportion of intercity transmission varied across cities from 0.14 (Yibin) and 1.00 (Ganzi). Stronger intercity transmission than average existed between some cities, e.g., between Deyang and Neijiang. CRF07_BC was the most widespread subtype between cities, and CRF85_BC (a novel HIV-1 subtype) showed strong intercity transmission (e.g., between Yibin and Guangan).InterpretationThe phylogenetic clustering rates and intercity connections of HIV-1 have varied geographically, possibly due to varying human mobility, traffic convenience, and economic activities. Our findings enhanced the understanding of the dynamics of HIV-1 transmission from individual to city level, and demonstrated a novel cross-disciplinary (epidemiological, genetic, and spatial) approach by which we identified high-risk populations and areas. Our approach could be adapted to other regions for precision public health interventions.FundingThe National Natural Science Foundation of China, Sichuan Science and Technology Program, Project of Sichuan Provincial Health Committee, Science and Technology Project of Sichuan Provincial Health Committee, Wuhan University 351 Talent Program, 2020, and the International Institute of Spatial Lifecourse Epidemiology (ISLE).

Spatial epidemiologic analysis of the liver cancer and gallbladder cancer incidence and its determinants in South Korea

BackgroundThere have been reports on regional variation in prevalence of hepatitis B and C, and Clonorchis sinensis (C. sinensis) infection, which indicates potential of spatial variation in liver cancer and gallbladder cancer incidence in Korea. Therefore, we aimed to assess the regional variation of liver and gallbladder cancer incidence and its determinants based on the regional distribution of risk factors, including hepatitis B infection in Korea.MethodsThis study used an ecological study design and district-level cancer incidence statistics generated by the National Cancer Center. Spatial clusters of liver and gallbladder cancer incidence were detected based on spatial scan statistics using SaTScan™ software. We set the size of maximum spatial scanning window of 25 and 35% of the population at risk for analyses of liver and gallbladder cancer, respectively. Significance level of 0.05 was used to reject the null hypothesis of no cluster. We fitted the Besag-York-Mollie model using integrated nested Laplace approximations to assess factors that influence the regional variation in cancer incidence.ResultsSpatial clusters with high liver cancer incidence rates were detected in the southwestern and southeastern regions of Korea. High gallbladder cancer incidence rates are clustered in the southeastern region. Regional liver cancer incidence can be accounted for the prevalence of high household income (coefficient, − 0.10; 95% credible interval [CI], − 0.18 to − 0.02), marital status (coefficient, − 0.14; 95% CI, − 0.25 to − 0.03), the incidence of hepatitis B (coefficient, 0.87; 95% CI, 0.29 to 1.44), and liver cancer screening (coefficient, 0.06; 95% CI, 0.00 to 0.12), while gallbladder cancer incidence was related to the prevalence of high household income (coefficient, − 0.03; 95% CI, − 0.05 to 0.00) and living close to a river with a high prevalence of liver fluke infection (coefficient, 0.55; 95% CI, 0.14 to 0.96).ConclusionsThis study demonstrated geographic variation in liver and gallbladder cancer incidence, which can be explained by determinants such as hepatitis B, income, marital status, and living near a river.

Spatial epidemiological study of the distribution, clustering, and risk factors associated with early COVID-19 mortality in Mexico.

COVID-19 is a respiratory disease caused by SARS-CoV-2, which has significantly impacted economic and public healthcare systems worldwide. SARS-CoV-2 is highly lethal in older adults (>65 years old) and in cases with underlying medical conditions, including chronic respiratory diseases, immunosuppression, and cardio-metabolic diseases, including severe obesity, diabetes, and hypertension. The course of the COVID-19 pandemic in Mexico has led to many fatal cases in younger patients attributable to cardio-metabolic conditions. Thus, in the present study, we aimed to perform an early spatial epidemiological analysis for the COVID-19 outbreak in Mexico. Firstly, to evaluate how mortality risk from COVID-19 among tested individuals (MRt) is geographically distributed and secondly, to analyze the association of spatial predictors of MRt across different states in Mexico, controlling for the severity of the disease. Among health-related variables, diabetes and obesity were positively associated with COVID-19 fatality. When analyzing Mexico as a whole, we identified that both the percentages of external and internal migration had positive associations with early COVID-19 mortality risk with external migration having the second-highest positive association. As an indirect measure of urbanicity, population density, and overcrowding in households, the physicians-to-population ratio has the highest positive association with MRt. In contrast, the percentage of individuals in the age group between 10 to 39 years had a negative association with MRt. Geographically, Quintana Roo, Baja California, Chihuahua, and Tabasco (until April 2020) had higher MRt and standardized mortality ratios, suggesting that risks in these states were above what was nationally expected. Additionally, the strength of the association between some spatial predictors and the COVID-19 fatality risk varied by zone.

High Level of Nitrogen Dioxide in Ambient Air Increased Incidence of Influenza in Children: An Observational Study in China

Background: The roles of air pollutants including nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone (O3) in influenza incidence at nationwide level of China remained obscure. Methods: Data from two complementary nation-wide influenza surveillance systems were applied to examine the association between air pollutants and influenza incidences. Spatial epidemiological analyses were performed on both air pollutants and influenza incidences in 31 provinces of mainland China. Cities with consistent data patterns between the two surveillance systems were chosen to examine the effects of pollutants on monthly influenza incidences using generalized estimating equations (GEE) and on daily incidence using the distributed lag non-linear model (DLNM). Results: Out of five common air pollutants (NO2, SO2, O3, CO, PM2.5), the concentration of NO2 was found spatially correlated with annual average influenza positive rates at province level (Pearson’s correlation coefficient=0.69, P<0.001). Based on data from 134 cities, NO2 and SO2 were found positively associated with monthly influenza incidences with estimated RRs of 1.22 and 1.09, respectively. The RRs increased to 1.45 and 1.13 among children younger than 18 years. NO2 is the only pollutant that showed robust positive association with daily influenza incidence in 12 of the 18 cities with adequate daily incidence data. The positive association was found in children under 18 years but not in adults. Interpretation: A higher NO2 concentration in ambient air was associated with an increased incidence of influenza across a wide geographic range in China with more vulnerable impact in Children. These findings reflect the need for annual vaccination campaign among children and their parents as well as air pollution control in densely populated urban areas. Funding Information: The National Natural Science Foundation of China; The China Mega-Project on Infectious Disease Prevention; The Key Research and Development Program of China; The US National Institutes of Health grant. Declaration of Interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organization for the submitted work; no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. Ethics Approval Statement: The current study was approved by Beijing Institute of Microbiology and Epidemiology in accordance with the medical research regulations of China.