The association between gun shows and firearm injuries: An analysis of 259 gun shows across 23 US cities.

Guns shows are estimated to account for 4-9% of firearm sales in the US. Increased regulation of firearm sales at gun shows has been proposed as one approach to reducing firearm injury rates. This study evaluated the association between gun shows and local firearm injury rates. Data regarding the date and location of gun shows from 2017 to 2019 were abstracted from the Big Show Journal. Firearm injury rates were estimated using discharges from trauma centers serving counties within a 25-mile radius of each gun show. Clinical data were derived from the National Trauma Databank (NTDB). We used Poisson regression modeling to adjust for potential confounders including seasonality. We evaluated injury rates before and after 259 gun shows in 23 US locations using firearm injury data from 36 trauma centers. There were 1513 hospitalizations for firearm injuries pre-gun show and 1526 post-gun show. The adjusted mean 2-week rate of all-cause firearm injury per 1,000,000 person-years was 1.79 (1.16-2.76) before and 1.82 (1.18-2.83) after a gun show, with an incident rate ratio of 1.02 (0.94, 1.08). The adjusted mean 2-week rate did not vary significantly by intent after a gun show, (p = 0.24). Within two weeks after a gun show, rates of hospitalization for all-cause firearm injury do not increase significantly within the surrounding communities. The relatively small increase in available firearms after a show and the short time horizon evaluated may account for the absence of an association between gun show firearm sales and local firearm injury rates.

Correlation between human development index and its components with COVID-19 indices: a global level ecologic study.

BACKGROUND: Given that COVID-19 continues to spread worldwide, attempts to restrain the virus and to prevent the effects that critically ill patients with COVID-19 have on healthcare systems, has become a public health priority. This ecological study aimed to investigate the correlation between the Human Development Index (HDI) and the epidemiological indicators of COVID-19, including the cumulative incidence rate of cases, the cumulative incidence rate of death, performed COVID-19 tests per million, recovery rate, and case fatality rate. METHODS: In this ecological study, a data set was provided, which included the epidemiologic indices of COVID-19, HDI, and its components for each country. Correlation coefficients were used to determine linear correlation. Also, the scatter plots of the HDI for the studied countries based on the epidemiologic indices of COVID-19 were drawn. RESULTS: This study showed that HDI and its components had positive correlation with a cumulative incidence rate of cases, the cumulative incidence rate of death, and performed COVID-19 tests (p < 0.001). HDI and two of its components, including literacy and Gross National Income (GNI) components had negative correlation with case fatality rate (CFR). Also, HDI and two of its components, including literacy and life expectancy components had negative correlation with recovery rate. CONCLUSION: Our study showed that the HDI and its components can affect the epidemiological status of COVID-19. As HDI increased, the cumulative incidence rate of cases, cumulative incidence rate of death, and COVID-19 tests increased as well. As HDI increased, CFR and recovery rate decreased as well. Although the HDI is higher in high-income countries, these countries may have also better reporting and surveillance systems.

Taking the inner route: spatial and demographic factors affecting vulnerability to COVID-19 among 604 cities from inner São Paulo State, Brazil.

Even though the impact of COVID-19 in metropolitan areas has been extensively studied, the geographic spread to smaller cities is also of great concern. We conducted an ecological study aimed at identifying predictors of early introduction, incidence rates of COVID-19 and mortality (up to 8 May 2020) among 604 municipalities in inner São Paulo State, Brazil. Socio-demographic indexes, road distance to the state capital and a classification of regional relevance were included in predictive models for time to COVID-19 introduction (Cox regression), incidence and mortality rates (zero-inflated binomial negative regression). In multivariable analyses, greater demographic density and higher classification of regional relevance were associated with both early introduction and increased rates of COVID-19 incidence and mortality. Other predictive factors varied, but distance from the State Capital (São Paulo City) was negatively associated with time-to-introduction and with incidence rates of COVID-19. Our results reinforce the hypothesis of two patterns of geographical spread of SARS-Cov-2 infection: one that is spatial (from the metropolitan area into the inner state) and another which is hierarchical (from urban centres of regional relevance to smaller and less connected municipalities). Those findings may apply to other settings, especially in developing and highly heterogeneous countries, and point to a potential benefit from strengthening non-pharmaceutical control strategies in areas of greater risk.

Factors behind the success story of under-five stunting in Peru: a district ecological multilevel analysis.

BACKGROUND: Stunting prevalence in children less than 5 years has remained stagnated in Peru from 1992 to 2007, with a rapid reduction thereafter. We aimed to assess the role of different predictors on stunting reduction over time and across departments, from 2000 to 2012. METHODS: We used various secondary data sources to describe time trends of stunting and of possible predictors that included distal to proximal determinants. We determined a ranking of departments by annual change of stunting and of different predictors. To account for variation over time and across departments, we used an ecological hierarchical approach based on a multilevel mixed-effects regression model, considering stunting as the outcome. Our unit of analysis was one department-year. RESULTS: Stunting followed a decreasing trend in all departments, with differing slopes. The reduction pace was higher from 2007-2008 onwards. The departments with the highest annual stunting reduction were Cusco (-2.31%), Amazonas (-1.57%), Puno (-1.54%), Huanuco (-1.52%), and Ancash (-1.44). Those with the lowest reduction were Ica (-0.67%), Ucayali (-0.64%), Tumbes (-0.45%), Lima (-0.37%), and Tacna (-0.31%). Amazon and Andean departments, with the highest baseline poverty rates and concentrating the highest rural populations, showed the highest stunting reduction. In the multilevel analysis, when accounting for confounding, social determinants seemed to be the most important factors influencing annual stunting reduction, with significant variation between departments. CONCLUSIONS: Stunting reduction may be explained by the adoption of anti-poverty policies and sustained implementation of equitable crosscutting interventions, with focus on poorest areas. Inclusion of quality indicators for reproductive, maternal, neonatal and child health interventions may enable further analyses to show the influence of these factors. After a long stagnation period, Peru reduced dramatically its national and departmental stunting prevalence, thanks to a combination of social determinants and crosscutting factors. This experience offers useful lessons to other countries trying to improve their children's nutrition.

[Ecological Trendofthe Incidence of Tuberculosis in Mianyang City During 2004-2013].

OBJECTIVES: To determine the trend of the incidence of tuberculosis (TB) in Mianyang City during 2004-2013 and its ecological determinants. METHODS: Linear correlations between TB incidence and ecological factors were analyzed using the data collected in Mianyang City from 2004 to 2013. A multivariate linear regression model was established to determine the ecological predictors of TB incidence. RESULTS: The incidence of TB in Mianyang City decreased over the period of 2004-2013. Economic development and increased health resources were negatively correlated with TB incidence. Population density was positively correlated with TB incidence. A multivariate linear regression equationon TB incidence (y) was established with the independent variables (x1 to x10) forming a component (using principal component analysis) to eliminate multicollinearity: y=117.692-1.467x1-1.145x2-1.961x3-4.777x4-2.690x5-6.181x6+82.234x7-2.721x8-0.351x9-0.382x10. The incidence of TB decreased with the increases of real GDP per capita (x1), average wage of workers(x2), per capita disposable income of urban residents (x3), rural per capita net income (x4), per capita consumption expenditure of urban residents (x5), per capita living consumption expenditure of rural residents (x6), number of licensed (assistant) physicians per thousand population (x8), urbanization rate (x9),and per capita housing construction area of urban (x10),while it increased with the increase of density of population (x7). CONCLUSIONS: Socio-economic development, health resources and population density are predictors of TB incidence.

Analysis of Differences in Characteristics of High-Risk Endemic Areas for Contracting Japanese Spotted Fever, Tsutsugamushi Disease, and Severe Fever With Thrombocytopenia Syndrome.

Background: Tick-borne infections, including tsutsugamushi disease, Japanese spotted fever, and severe fever with thrombocytopenia syndrome (SFTS), are prevalent in East Asia with varying geographic distribution and seasonality. This study aimed to investigate the differences in the characteristics among endemic areas for contracting each infection. Methods: We conducted an ecologic study in Japan, using data from a nationwide inpatient database and publicly available geospatial data. We identified 4493 patients who were hospitalized for tick-borne infections between July 2010 and March 2021. Mixed-effects modified Poisson regression analysis was used to identify factors associated with a higher risk of contracting each tick-borne disease (Tsutsugamushi, Japanese spotted fever, and SFTS). Results: Mixed-effects modified Poisson regression analysis revealed that environmental factors, such as temperature, sunlight duration, elevation, precipitation, and vegetation, were associated with the risk of contracting these diseases. Tsutsugamushi disease was positively associated with higher temperatures, farms, and forests, whereas Japanese spotted fever and SFTS were positively associated with higher solar radiation and forests. Conclusions: Our findings from this ecologic study indicate that different environmental factors play a significant role in the risk of transmission of tick-borne infections. Understanding the differences can aid in identifying high-risk areas and developing public health strategies for infection prevention. Further research is needed to address causal relationships.

Correlation Between Diabetes and COVID-19 Indices: A Global Level Ecological Study.

Introduction: Coronavirus is threatening the global public health as a new and widespread crisis. The researchers must keep in mind that one of the most vulnerable groups to COVID-19 are the people with underlying diseases, especially diabetes. Objective: This ecological study aimed to investigate the correlation between diabetes and the epidemiological indices of COVID-19. Methods: This ecological study included 144 countries. Their available data consists of the cumulative incidence rate of cases, cumulative incidence rate of death, recovery rate, case fatality rate, and performed tests of COVID-19, and diabetes. To collect the variables, a data set was provided which included the information of 144 countries based on diabetes and COVID-19 indices. Spearman coefficients were used for assess correlation between diabetes and COVID-19 indices. Also, Scatter plots of diabetes for the studied countries were drawn based on cumulative incidence rate of cases, cumulative incidence rate of death, tests, recovery rate, and case fatality rate of COVID-19. Results: The results of this ecological study showed in total countries, there was a weak positive correlation between diabetes and cumulative incidence rate of cases and also cumulative incidence rate of death. Correlation between diabetes with test of COVID-19 was very weak. Scatter plots showed a weak liner correlation between diabetes and cumulative incidence rate of cases, cumulative incidence rate of death and test of COVID-19. Conclusions: In this study, there was a weak positive correlation between diabetes and cumulative incidence rate of cases, cumulative incidence rate of death, and performed test of COVID-19. This disease is an enormous challenge for health policymakers; therefore, it is necessary to develop strategies and practical guidelines specific to each region to take the necessary care, especially for diabetic patients.

Morbidity and mortality of COVID-19 negatively associated with the frequency of consanguineous marriages, an ecologic study.

Background: Union between second cousins and closer relatives is called consanguineous marriage. Consanguineous marriage is associated with increased risk of autosomal recessive diseases and several multifactorial traits. In order to evaluate the association between prevalence/mortality of COVID-19 and the frequency of consanguineous marriage, the present ecologic study was carried out. For the present study, data of prevalence (per 106 people) and mortality (per 106 people) and number of performed laboratory diagnostic test (per 106 people) of COVID-19 disease at four time points (December 2020; March, August and October 2021) of 65 countries were used. Results: Univariable correlation and generalized estimating equation analysis were used. In analysis, prevalence and mortality of COVID-19 were used as dependent variables and human development index, number of performed diagnosis test and the mean of inbreeding coefficient (α-value) were introduced into model as covariates, and time point was used as a factor in analysis. The square root (SR) of prevalence (P = 0.008) and SR-mortality (P < 0.001) of COVID-19 negatively associated with the log-transformed of α-value. Conclusions: The present finding means that in countries with high levels of consanguineous marriages, the prevalence of COVID-19 and mortality due to COVID-19 were lower than countries having low level of marriage with relatives.

Correlation between environmental factors and COVID-19 indices: a global level ecological study.

This global level ecological study aimed to investigate the correlation between environmental factors and the COVID-19 indices. This survey is an ecological study, so all studied variables are aggregate variables. To collect the variables in the study, a data set was provided, which includes the information of each country based on the cumulative deaths, case fatality rate, recovery rate, and the number of performed COVID-19 tests. Scatter plots of environmental factors for the studied countries were drawn based on cumulative incidence rate of cases, cumulative incidence rate of death, tests, recovery rate, and case fatality rate of COVID-19. Furthermore, Spearman correlation coefficient was also used to verify the correlation between environmental factors and indicators related to COVID-19. The results of this ecological study showed that among all countries surveyed, Montenegro (60,310.56 per million) and Luxembourg (54,807.89 per million) had the highest cumulative incidence rates of COVID-19 cases, when Tanzania (8.42 per million) and Vietnam (13.78 per million) had the lowest cumulative incidence rates of COVID-19. In addition, in this study, it was shown that the cumulative incidence rate of cases, the cumulative incidence rate of deaths, and performed COVID-19 tests had significant direct correlations with the access to drinking water and the access to sanitation services (p < 0.001). The findings of the present study showed an inverse correlation between the mortality rate due to unhealthy water consumption, poor health status, and a positive correlation between access to drinking water and health services with the cumulative incidence and mortality rates of COVID-19. The differences between our findings and many other studies could be due to the ecological nature of the study. Nevertheless, our findings will help health policymakers to develop timely strategies to reduce the mortality and incidence rate of COVID-19.

The Association between Ambient PM2.5 and Low Birth Weight in California.

Previous studies have shown associations between air pollutants and low birth weight. However, few studies assess whether poverty and race/ethnicity are effect modifiers for this relationship. We used publicly available data on 7785 California census tracts from the California Communities Environmental Health Screening Tool (CalEnviroScreen). Multivariable linear regression was used to examine the association between outdoor PM2.5 and low birth weight (LBW), including stratification by poverty and race/ethnicity (as a proxy for experienced racism). A 1 µg m-3 increase in PM2.5 was associated with a 0.03% (95% CI: 0.01, 0.04) increase in the percentage of LBW infants in a census tract. The association between PM2.5 and LBW was stronger in census tracts with the majority living in poverty (0.06% increase; 95% CI: 0.03, 0.08) compared to those with fewer people living in poverty (0.02% increase; 95% CI: 0.00, 0.03). Our results show that exposure to outdoor PM2.5 is associated with a small increase in the percentage of LBW infants in a census tract, with a further increase in tracts with high poverty. The results for effect modification by race/ethnicity were less conclusive.

The correlation between attack rates and urban health indicators during the third wave of the COVID-19 outbreak in Turkey.

This study aims to analyze the inter-provincial variation in the increase of attack rates in the third wave of the COVID-19 outbreak in Turkey and to determine their relationship with potential urban health indicators. In this ecological study, dependent variables were selected as the COVID-19 attack rates of provinces before the third wave and during the third peak and the attack rate increase ratio. Urban health indicators that can function as determinants of health were calculated for each province under five headings: demographic, health capacity, economic, environmental, and socio-cultural. The epidemiologic maps were produced to show the spatial distribution of COVID-19 attack rates pre- and during the third wave. The associations with urban indicators were conducted using bivariate analysis, including Pearson or Spearman correlation analysis. A multiple linear regression model was run with variables significantly associated with increased attack rates. The results of our study show significant regional variations in COVID-19 attack rates both at the beginning and during the third wave of the COVID-19 pandemic in Turkey. Among the provinces, the attack rate increase ratio has only shown significant correlations to education level and some economic indicators, such as income, employment, industrial activity measured by electric consumption, and economic activity in the manufacturing industry. The multivariate analysis determined that the indicator of economic activity in the manufacturing industry is related to the increase of the attack rate in the third wave. Our results show that the COVID-19 cases are higher in more developed cities with more manufacturing sector activity. It makes us think that it is mainly related to inequalities arising from access to health institutions and testing. It can be determined that the partly lockdown strategy, which excluded the industrial activity in the country, concluded the higher increase in the attack rates in highly industrialized provinces.

Why Are COVID-19 Mortality Rates by Country or Region So Different?: An Ecologic Study of Factors Associated with Mortality from Novel Coronavirus Infections by Country.

BACKGROUND: In order to find out the factors associated with the large disparities in COVID-19 mortality rates by country, we conducted an ecological study by linking existing statistics. In Japan, a large variation was observed in between geographical areas when assessing mortality. We performed a regional correlation analysis to find factors related to regional mortality. METHODS: This study design was an ecologic study. A multiple regression analysis was performed with COVID-19 mortality rates of different countries as the dependent variable together with various health care and economic factors. We calculated the cumulative mortality rate as of June 30, 2020. For the regional correlation analysis of Japan, 47 prefectures were divided into nine regions. The factors examined were health care and tourism. Data for 33 Organization for Economic Co-operation and Development (OECD) countries were analyzed. In Japan's regional analysis, the whole country was classified into nine regions. RESULTS: Factors related to mortality were the incidence of Kawasaki disease (KD), number of computed tomographies (CTs), and alcohol consumption. Mortality was low in countries with high incidence of KD and high number of CTs, as well as in countries with high alcohol consumption. In European countries, high smoking prevalence and a high Gini coefficient were positively related to high mortality. According to a regional analysis in Japan, mortality was related to proportion of population in the densely inhabited districts, the number of foreign visitors per capita, and the number of Chinese visitors per capita. CONCLUSION: Low mortality in East Asia was associated with specific disease morbidity (KD), alcohol consumption, and CT numbers. It was suggested that the mortality gap in Japan was related to the number of foreign tourists and the proportion of population in the densely inhabited districts.

Social Distancing Associations with COVID-19 Infection and Mortality Are Modified by Crowding and Socioeconomic Status.

The SARS-CoV-2 virus is a public health emergency. Social distancing is a key approach to slowing disease transmission. However, more evidence is needed on its efficacy, and little is known on the types of areas where it is more or less effective. We obtained county-level data on COVID-19 incidence and mortality during the first wave, smartphone-based average social distancing (0-5, where higher numbers indicate more social distancing), and census data on demographics and socioeconomic status. Using generalized linear mixed models with a Poisson distribution, we modeled associations between social distancing and COVID-19 incidence and mortality, and multiplicative interaction terms to assess effect modification. In multivariable models, each unit increase in social distancing was associated with a 26% decrease (p < 0.0001) in COVID-19 incidence and a 31% decrease (p < 0.0001) in COVID-19 mortality. Percent crowding, minority population, and median household income were all statistically significant effect modifiers. County-level increases in social distancing led to reductions in COVID-19 incidence and mortality but were most effective in counties with lower percentages of black residents, higher median household incomes, and with lower levels of household crowding.

The morbidity and mortality of COVID-19 are correlated with the Ile105Val glutathione S-transferase P1 polymorphism.

Background: Oxidative stress is an important issue in coronavirus disease 2019 (COVID-19). Considering that glutathione S-transferase P1 (GSTP1) is involved in cellular detoxification, it may play an important role in susceptibility to infection with SARS-CoV-2 and/or its outcome. In the present study, the association between the Ile105Val GSTP1 polymorphism (rs1695) and susceptibility to SARS-CoV-2 infection, as well as its outcome was investigated. Data on the prevalence (per 106 people), case-fatality (per 100 infected cases), and mortality (per 106 people) of COVID-19 and various potential confounders (the life expectancy at birth, density of medical doctors, density of nursing and midwifery personnel, and the gross national income per capita) were used. The latest data available for 45 countries were used for the study. Results: In multivariate linear regression analyses, the Val105 allelic frequency showed positive association with the log-prevalence (partial r = 0.308, p = 0.042) and log-mortality of COVID-19 (partial r = 0.316, p = 0.037). The log-fatality did not show association with the allelic frequency. In the next step, only countries with the gross national income per capita more than $15,000 were included in the analysis. In the selected countries, the frequency of Val105 was positively associated with the log-prevalence (partial r = 0.456, p = 0.009) and log-mortality of COVID-19 (partial r = 0.544, p = 0.001). Conclusions: The present findings indicate that countries with higher Val105 allelic frequency of the rs1695 polymorphism showed higher prevalence and mortality of COVID-19.

Geographical clusters and social risk factors for suicide in the city of São Paulo, 2006-2015: An ecologic study.

BACKGROUND: To identify geographical clusters of suicide in São Paulo, Brazil (2006-2015) and to verify the associations of suicide with sociocultural characteristics of its 96 districts. METHODS: Spatial scan test was used to detect the geographical clusters. Correlation and multiple regression techniques were used to estimate the association of socioeconomic and cultural variables with suicide. RESULTS: The mean suicide rate was 4.8/100,000. Three clusters were identified which are as follows: one of increased risk in downtown and two of decreased risk in the South and in the Southeast. The mean suicide rate of the high-risk clustered districts (7.99/100,000) presented significantly higher average incomes per household, higher proportion of formally educated, of no religious affiliation, of recent migrants, of all-times migrants and lower proportion of married. The multiple model selected two independent risk factors - people with no religious affiliation (ß = 0.182) and of recent migrants (ß = 0.278) - and two protective factors - the proportion of married (ß = -0.185) and of total migrants (ß = -0.075), which jointly explained 58.4% of the variance. CONCLUSION: Durkheimian social and cultural risk factors for suicide were confirmed. Compared to a previous study period (1996-2005), suicide rates and geographical clusters remained relatively stable in the subsequent decade (2006-2015).

Worldwide Disparity in the Relation Between CKD Prevalence and Kidney Failure Risk.

INTRODUCTION: The incidence of kidney replacement therapy (KRT) for kidney failure varies internationally much more than chronic kidney disease (CKD) prevalence. This ecologic study investigated the relation of CKD prevalence to KRT and mortality risks by world region. METHODS: We used data from Global Burden of Disease and KRT registries worldwide with linear models to estimate the percentages of variance in KRT incidence and all-cause mortality explained by age-adjusted prevalence of CKD stages 3 to 5, overall and by gender, in 61 countries classified in 3 regions: high income (n = 28), Eastern and Central Europe (n = 15), and other (n = 18). RESULTS: The incidence of KRT ranged from 89 to 378 per million population in high-income regions, 32 to 222 per million population in Central and Eastern Europe, and 22 to 493 per million population in the other region; age-adjusted CKD prevalence ranged from 5.5% to 10.4%, 7.6% to 13.7%, and 7.4% to 13.1%, respectively. The relation between these indicators was positive in high-income countries, negative in Central and Eastern Europe, and null in the other region. Age-adjusted CKD prevalence explained 40% of the variance in KRT incidence (P < 0.001) in high-income countries. The explained variance of age-adjusted mortality was close to 0 in high-income countries and positive at 19% (P = 0.10) in Central and Eastern Europe and at 11% (P = 0.17) in the other region. Results were consistent by gender. CONCLUSION: This study raises awareness on the significant part of the gaps in KRT incidence across countries not explained by the number of individuals with CKD, even in high-income countries where access to KRT is not limited.

Mammography Coverage and Tumor Stage in the Opportunistic Screening Context.

INTRODUCTION: The increment of breast cancer screening coverage should lead to an increase in the proportion of early tumors diagnosed and the decrease of the cancer-related mortality. However, the effectiveness of opportunistic mammography screening is not well documented for public health systems in middle-income countries. PATIENTS AND METHODS: We conducted an ecologic study to evaluate the association of mammography coverage with trends in breast cancer stage distribution. We used data from a total of 42,850 breast cancer patients, diagnosed between 2000 and 2016, combined with estimated mammography coverage from 3 surveys (2003, 2008, and 2013). RESULTS: Biannual mammography coverage increased from 62.4% in 2003 to 73.9% in 2013. From 2000 to 2016, the proportion of in situ tumors increased 6.9%, the proportion of localized tumors increased 3.9%, the proportion of regional tumors decreased 6.9% and the frequency of distant tumors decreased 4% (P < .00001). CONCLUSION: Mammography coverage in the context of opportunistic breast cancer screening was associated with the increase of in situ and localized tumors and decrease of regional and distant tumors.

Spatial distribution of Robson 10-group classification system and poverty in southern and southeastern Brazil.

OBJECTIVE: To assess the spatial distribution of the Robson 10-group classification system (TGCS) and poverty in southeastern and southern regions of Brazil in 2016. METHODS: An ecologic study based on public data from the Brazilian Information System on Live Births and the Brazilian Institute of Geography and Statistics, including 1 519 289 (53.2%) of all live-born neonates in Brazil between January and December 2016. Statistical analysis used Bayesian modelling with spatial distribution following an autoregressive conditional structure, and Moran index. RESULTS: In 2016, the percentage of live-born neonates delivered by cesarean was 58.8% and 60.7% in the southeastern and southern regions, respectively. Robson groups 1 and 3, involving spontaneous labor, were related to regions with higher poverty (Moran index, 0.36 and 0.44, respectively), whereas groups 2 and 5, involving cesarean delivery, were related to poorer regions (Moran index, 0.56 and 0.45, respectively). CONCLUSION: The frequencies of each group of the Robson TGCS were heterogeneously distributed in the geographic space owing to important associations with the proportion of poverty in the different regions. Actions are needed to develop the poorest regions in order to minimize existing disparities.

A Predictive Model Has Identified Tick-Borne Encephalitis High-Risk Areas in Regions Where No Cases Were Reported Previously, Poland, 1999-2012.

During 1999­2012, 77% of the cases of tick-borne encephalitis (TBE) were recorded in two out of 16 Polish provinces. However, historical data, mostly from national serosurveys, suggest that the disease could be undetected in many areas. The aim of this study was to identify which routinely-measured meteorological, environmental, and socio-economic factors are associated to TBE human risk across Poland, with a particular focus on areas reporting few cases, but where serosurveys suggest higher incidence. We fitted a zero-inflated Poisson model using data on TBE incidence recorded in 108 NUTS-5 administrative units in high-risk areas over the period 1999­2012. Subsequently we applied the best fitting model to all Polish municipalities. Keeping the remaining variables constant, the predicted rate increased with the increase of air temperature over the previous 10­20 days, precipitation over the previous 20­30 days, in forestation, forest edge density, forest road density, and unemployment. The predicted rate decreased with increasing distance from forests. The map of predicted rates was consistent with the established risk areas. It predicted, however, high rates in provinces considered TBE-free. We recommend raising awareness among physicians working in the predicted high-risk areas and considering routine use of household animal surveys for risk mapping.

Geographical Clusters and Predictors of Rabies in Three Southeastern States.

The rabies virus causes progressive encephalomyelitis that is fatal in nearly 100% of untreated cases. In the United States, wildlife act as the primary reservoir for rabies; prevention, surveillance, and control costs remain high. The purpose of this study is to understand the current distribution of wildlife rabies in three southeastern states, with particular focus on raccoons as the primary eastern reservoir, as well as identify demographic and geographic factors which may affect the risk of human exposure. This ecologic study obtained county-level rabies surveillance data from state health departments and the United States Department of Agriculture Wildlife services for North Carolina, Virginia, and West Virginia from 2010 to 2013. A spatial statistical analysis was performed to identify county clusters with high or low rates of raccoon rabies in the three states. Potential demographic and geographic factors associated with these varying rates of rabies were assessed using a multivariable negative binomial regression model. In North Carolina, raccoons constituted 50% of positive tests, in Virginia, 49%, and in West Virginia, 50%. Compared to persons residing in West Virginia counties, persons in North Carolina counties had 1.67 times the risk of exposure (p < 0.0001) to a rabid raccoon and those in Virginia counties had 1.82 times the risk of exposure (p < 0.0001) to a rabid raccoon. Compared to those counties where farmland makes up less than 17% of the total area, persons residing in counties with 17-28% farmland had a 32% increased risk of exposure to a rabid raccoon. In counties with 28-39% farmland, there was an 84% increased risk of exposure. State, rurality, and percent of area designated as farmland were the best predictors of risk of raccoon rabies exposure. Further research is needed to better understand the effect of the oral rabies vaccine program in controlling the risk of human exposure to raccoon rabies.