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.

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.

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 PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 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.

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.

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.

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.

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 (β = 0.182) and of recent migrants (β = 0.278) - and two protective factors - the proportion of married (β = -0.185) and of total migrants (β = -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).

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.

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

During 1999–2012, 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 1999–2012. 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 10–20 days, precipitation over the previous 20–30 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.

An ecological analysis of PM2.5 concentrations and lung cancer mortality rates in China

OBJECTIVE

To explore the association between Particulate Matter (PM)2.5 (particles with an aerodynamic diameter less than 2.5 µm) and lung cancer mortality rates and to estimate the potential risk of lung cancer mortality related to exposure to high PM2.5 concentrations.

DESIGN

Geographically weighted regression was performed to evaluate the relation between PM2.5 concentrations and lung cancer mortality for males, females and for both sexes combined, in 2008, based on newly available long-term data. Lung cancer fatalities from long-term exposure to PM2.5 were calculated according to studies by Pope III et al and the WHO air quality guidelines (AQGs).

SETTING

31 provinces in China.

RESULTS

PM2.5 was associated with the lung cancer mortality of males, females and both sexes combined, in China, although there were exceptions in several regions, for males and females. The number of lung cancer fatalities calculated by the WHO AQGs ranged from 531,036 to 532,004, whereas the number calculated by the American Cancer Society (ACS) reached 614,860 after long-term (approximately 3-4 years) exposure to PM2.5 concentrations since 2008.

CONCLUSIONS

There is a positive correlation between PM2.5 and lung cancer mortality rate, and the relationship between them varies across the entire country of China. The number of lung cancer fatalities estimated by ACS was closer to the actual data than those of the WHO AQGs. Therefore, the ACS estimate of increased risk of lung cancer mortality from long-term exposure to PM2.5 might be more applicable for evaluating lung cancer fatalities in China than the WHO estimate.

Does level of tobacco control relate to smoking prevalence in Canada: a national survey of public health organizations

OBJECTIVES

To describe levels of tobacco control "effort" in public health organizations across provinces, and to test the hypothesis that "effort" is associated with the prevalence of daily smoking.

METHODS

Data were drawn from a national survey (Oct 2004-Apr 2005) of all public health organizations engaged in chronic disease prevention in Canada in 2004. We investigated the association between "effort" and decline in smoking prevalence (CTUMS, 1999-2009) across provinces in an ecologic study design. "Effort" was assessed using two indicators: percent of public health organizations engaged in tobacco control, and mean level of involvement in engaged organizations.

RESULTS

Of 216 organizations, 88% had undertaken tobacco control activities in the three years prior to data collection and were categorized as "engaged". Level of involvement in tobacco control was highest in community-at-large settings; and it was generally higher for population- than for individual-level strategies. Nova Scotia reported higher levels of involvement than other provinces. There was substantial variability in "effort" across provinces. High-"effort" provinces (BC, NS, ON, QC) experienced, on average, improvement in the "change in smoking prevalence" score (1999 to 2009).

CONCLUSION

The findings provide evidence that provincial tobacco control "effort" relates to declines in smoking prevalence. Given that smoking remains a critical public health issue, the kinds of data reported herein are needed to inform the debate on how best to invest in tobacco control infrastructure to combat the most important public health threat of our times.

A European study on the relationship between antimicrobial use and antimicrobial resistance

In Europe, antimicrobial resistance has been monitored since 1998 by the European Antimicrobial Resistance Surveillance System (EARSS). We examined the relationship between penicillin nonsusceptibility of invasive isolates of Streptococcus pneumoniae and antibiotic sales. Information was collected on 1998-99 resistance data for invasive isolates of S. pneumoniae to penicillin, based on surveillance data from EARSS and on outpatient sales during 1997 for beta-lactam antibiotics and macrolides. Our results show that in Europe antimicrobial resistance of S. pneumoniae to penicillin is correlated with use of beta-lactam antibiotics and macrolides.

Ecologic study of lung cancer risk factors in the U.S. and Japan, with special reference to smoking and diet

Lung cancer mortality rates among United States and Japanese males were compared and related to smoking and dietary data. Mortality rates increased from 1950 to 1985 in both countries, but the absolute values are consistently lower in Japan (38.2 deaths/100,000 in 1985) than in the U.S. (72.2/100,000). The proportion of smokers is higher in Japan than in the U.S. since 1955. Japanese males start smoking considerably later than U.S. males, but smoke a higher quantity of cigarettes per day. Available information on inhalation practices and yield and type of cigarettes smoked showed no differences among the two countries large enough to account for the differences in mortality rates. Further data in this regard should be obtained. Dietary data show that fat consumption (as percentage of calories) is consistently higher in the U.S. than in Japan from 1950 (40% vs. 7.9%) through 1985 (43.5% vs. 24.5%). A linear relationship is observed between lung cancer mortality and fat intake. Our data support the hypothesis that dietary habits may modulate the carcinogenic effects of tobacco smoking.