Community Susceptibility and Resiliency to COVID-19 Across the Rural-Urban Continuum in the United States

Purpose

This study creates a COVID‐19 susceptibility scale at the county level, describes its components, and then assesses the health and socioeconomic resiliency of susceptible places across the rural‐urban continuum.

Methods

Factor analysis grouped 11 indicators into 7 distinct susceptibility factors for 3,079 counties in the conterminous United States. Unconditional mean differences are assessed using a multivariate general linear model. Data from 2018 are primarily taken from the US Census Bureau and CDC.

Results

About 33% of rural counties are highly susceptible to COVID‐19, driven by older and health‐compromised populations, and care facilities for the elderly. Major vulnerabilities in rural counties include fewer physicians, lack of mental health services, higher disability, and more uninsured. Poor Internet access limits telemedicine. Lack of social capital and social services may hinder local pandemic recovery. Meat processing facilities drive risk in micropolitan counties. Although metropolitan counties are less susceptible due to healthier and younger populations, about 6% are at risk due to community spread from dense populations. Metropolitan vulnerabilities include minorities at higher health and diabetes risk, language barriers, being a transportation hub that helps spread infection, and acute housing distress.

Conclusions

There is an immediate need to know specific types of susceptibilities and vulnerabilities ahead of time to allow local and state health officials to plan and allocate resources accordingly. In rural areas it is essential to shelter‐in‐place vulnerable populations, whereas in large metropolitan areas general closure orders are needed to stop community spread. Pandemic response plans should address vulnerabilities.

Racial demographics and COVID-19 confirmed cases and deaths: a correlational analysis of 2886 US counties

Background

Recent news reports state that racial minority groups, such as African–Americans, are experiencing a greater COVID-19 burden, as measured by confirmed cases and deaths. Limited racial data is available on a national level.

Methods

We conducted the first nationwide analysis to examine COVID-19 and race on a county level. We obtained datasets on COVID-19 cases and deaths, and racial population totals, by US county. We examined if correlations exist between the racial percentages and percentages of confirmed COVID-19 cases and deaths by county.

Results

A positive correlation existed between percentages of African–Americans living in a county and who have COVID-19 (r = 0.254, P < 0.0001), who have died from COVID-19 (r = 0.268, P < 0.0001), and case mortality (r = 0.055, P = 0.003). Positive correlations also existed between percentages of Asian–Americans living in counties and these factors. Negative correlations existed between percentages of Whites living in counties and these factors.

Conclusions

A weak, albeit very significant, positive relationship exists between the percentage of African–Americans living in a county and the percentage of COVID-19 confirmed cases, confirmed deaths and case mortality in the county. This is in support of many city and statewide analyses, and we urge for targeted resources towards work that further examine these racial associations.

COVID-19 cases in US counties: roles of racial/ethnic density and residential segregation

OBJECTIVE

To investigate how racial/ethnic density and residential segregation shape the uneven burden of COVID-19 in US counties and whether (if yes, how) residential segregation moderates the association between racial/ethnic density and infections.

DESIGN

We first merge various risk factors from federal agencies (e.g. Census Bureau and Centers for Disease Control and Prevention) with COVID-19 cases as of June 13th in contiguous US counties (N = 3,042). We then apply negative binomial regression to the county-level dataset to test three interrelated research hypotheses and the moderating role of residential segregation is presented with a figure.

RESULTS

Several key results are obtained. (1) Counties with high racial/ethnic density of minority groups experience more confirmed cases than those with low levels of density. (2) High levels of residential segregation between whites and non-whites increase the number of COVID-19 infections in a county, net of other risk factors. (3) The relationship between racial/ethnic density and COVID-19 infections is enhanced with the increase in residential segregation between whites and non-whites in a county.

CONCLUSIONS

The pre-existing social structure like residential segregation may facilitate the spread of COVID-19 and aggravate racial/ethnic health disparities in infections. Minorities are disproportionately affected by the novel coronavirus and focusing on pre-existing social structures and discrimination in housing market may narrow the uneven burden across racial/ethnic groups.

The public sector nursing workforce in Kenya: a county-level analysis

BACKGROUND

Kenya's human resources for health shortage is well documented, yet in line with the new constitution, responsibility for health service delivery will be devolved to 47 new county administrations. This work describes the public sector nursing workforce likely to be inherited by the counties, and examines the relationships between nursing workforce density and key indicators.

METHODS

National nursing deployment data linked to nursing supply data were used and analyzed using statistical and geographical analysis software. Data on nurses deployed in national referral hospitals and on nurses deployed in non-public sector facilities were excluded from main analyses. The densities and characteristics of the public sector nurses across the counties were obtained and examined against an index of county remoteness, and the nursing densities were correlated with five key indicators.

RESULTS

Of the 16,371 nurses in the public non-tertiary sector, 76% are women and 53% are registered nurses, with 35% of the nurses aged 40 to 49 years. The nursing densities across counties range from 1.2 to 0.08 per 1,000 population. There are statistically significant associations of the nursing densities with a measure of health spending per capita (P value = 0.0028) and immunization rates (P value = 0.0018). A higher county remoteness index is associated with explaining lower female to male ratio of public sector nurses across counties (P value <0.0001).

CONCLUSIONS

An overall shortage of nurses (range of 1.2 to 0.08 per 1,000) in the public sector countrywide is complicated by mal-distribution and varying workforce characteristics (for example, age profile) across counties. All stakeholders should support improvements in human resources information systems and help address personnel shortages and mal-distribution if equitable, quality health-care delivery in the counties is to be achieved.

Enduring Cancer Disparities by Persistent Poverty, Rurality, and Race: 1990-1992 to 2014-2018

BACKGROUND

Most persistent poverty counties are rural and contain high concentrations of racial minorities. Cancer mortality across persistent poverty, rurality, and race is understudied.

METHODS

We gathered data on race and cancer deaths (all sites; lung and bronchus; colorectal; liver and intrahepatic bile duct; oropharyngeal; breast and cervical [females]; and prostate [males]) from National Death Index (1990-1992; 2014-2018). We linked these data to county characteristics: a) persistent poverty or not and b) rural or urban. We calculated absolute (range difference) and relative (range ratio) disparities for each cancer mortality outcome across persistent poverty, rurality, race, and time.

RESULTS

The 1990-1992 range difference for all sites combined indicated persistent poverty counties had 12.73 (95% confidence interval [CI]=11.37-14.09) excess deaths per 100,000 people/year compared to non-persistent poverty counties; the 2014-2018 range difference was 10.99 (95% CI = 10.22-11.77). Similarly, the 1990-1992 range ratio for all sites indicated mortality rates in persistent poverty counties were 1.06 (95% CI = 1.05-1.07) times as high as non-persistent poverty counties; the 2014-2018 range ratio was 1.07 (95% CI = 1.07-1.08). Between 1990-1992 and 2014-2018, absolute and relative disparities by persistent poverty widened for colorectal and breast cancers; however, for remaining outcomes, trends in disparities were stable or mixed. The highest mortality rates were observed among African American/Black residents of rural, persistent poverty counties for all sites, colorectal, oropharyngeal, breast, cervical, and prostate cancers.

CONCLUSIONS

Mortality disparities by persistent poverty endured over time for most cancer outcomes, particularly for racial minorities in rural, persistent poverty counties. Multisector interventions are needed to improve cancer outcomes.

Urban sprawl, obesity, and cancer mortality in the United States: cross-sectional analysis and methodological challenges

BACKGROUND

Urban sprawl has the potential to influence cancer mortality via direct and indirect effects on obesity, access to health services, physical activity, transportation choices and other correlates of sprawl and urbanization.

METHODS

This paper presents a cross-sectional analysis of associations between urban sprawl and cancer mortality in urban and suburban counties of the United States. This ecological analysis was designed to examine whether urban sprawl is associated with total and obesity-related cancer mortality and to what extent these associations differed in different regions of the US. A major focus of our analyses was to adequately account for spatial heterogeneity in mortality. Therefore, we fit a series of regression models, stratified by gender, successively testing for the presence of spatial heterogeneity. Our resulting models included county level variables related to race, smoking, obesity, access to health services, insurance status, socioeconomic position, and broad geographic region as well as a measure of urban sprawl and several interactions. Our most complex models also included random effects to account for any county-level spatial autocorrelation that remained unexplained by these variables.

RESULTS

Total cancer mortality rates were higher in less sprawling areas and contrary to our initial hypothesis; this was also true of obesity related cancers in six of seven U.S. regions (census divisions) where there were statistically significant associations between the sprawl index and mortality. We also found significant interactions (p < 0.05) between region and urban sprawl for total and obesity related cancer mortality in both sexes. Thus, the association between urban sprawl and cancer mortality differs in different regions of the US.

CONCLUSIONS

Despite higher levels of obesity in more sprawling counties in the US, mortality from obesity related cancer was not greater in such counties. Identification of disparities in cancer mortality within and between geographic regions is an ongoing public health challenge and an opportunity for further analytical work identifying potential causes of these disparities. Future analyses of urban sprawl and health outcomes should consider exploring regional and international variation in associations between sprawl and health.

The impact of antibiotic prescription rates on the incidence of MRSA bloodstream infections: A county-level, US-wide analysis

OBJECTIVES

To investigate the association of methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infection with socioeconomic factors and antibiotic prescriptions at the county level.

METHODS

MRSA bloodstream infection rates were extracted from the Medicare Hospital Compare database. Data on socioeconomic factors and antibiotic prescriptions were obtained from the US Census Bureau and the Medicare Part D database, respectively.

RESULTS

In multivariate analysis, antibiotic prescriptions demonstrated a powerful positive association with MRSA bloodstream infection rates [Coefficient (Coeff): 0.432, 95% Confidence Interval (CI): 0.389, 0.474, P < 0.001], which was largely attributable to lincosamides (Coeff: 0.257, 95% CI: 0.177, 0.336, P < 0.001), glycopeptides (Coeff: 0.223, 95% CI: 0.175, 0.272, P < 0.001), and sulfonamides (Coeff: 0.166, 95% CI: 0.082, 0.249, P < 0.001). Sociodemographic factors, such as poverty (Coeff: 0.094, 95% CI: 0.034, 0.155, P=0.002) exerted a secondary positive impact on MRSA bloodstream infection. Conversely, college education (Coeff: -0.037, 95% CI: -0.068, -0.005, P=0.024), a larger median room number per house (Coeff: -0.107, 95% CI: -0.134, -0.081, P < 0.001), and an income above the poverty line (100% < income < 150% of the poverty line) (Coeff: -0.257, 95% CI: -0.314, -0.199, P < 0.001) were negatively associated with MRSA incidence rates. A multivariate model that incorporated socioeconomic data and antibiotic prescription rates predicted 39.1% of the observed variation in MRSA bloodstream infection rates (Pmodel < 0.001).

CONCLUSIONS

MRSA bloodstream infection rates were strongly associated with county-level antibiotic use and socioeconomic factors. If the causality of these associations is confirmed, antimicrobial stewardship programs that extend outside acute healthcare facilities would likely prove instrumental in arresting the spread of MRSA.

County-Level Recreational Marijuana Policies and Local Policy Changes in Colorado and Washington State (2012-2019)

Policy Points In 2012, Colorado and Washington were the first states to legalize recreational marijuana through voter-initiated ballots. In these states, counties could restrict or ban local marijuana facilities through a variety of regulatory methods such as ordinances and zoning. County-level recreational marijuana policies in Washington and Colorado vary substantially, with 69.2% of Washington counties and 23.4% of Colorado counties allowing all types of recreational marijuana facilities as of April 1, 2019. After Colorado and Washington legalized recreational marijuana, many counties modified their marijuana policies over time, with shifts in county policy often preceded by advocacy and information-seeking activities.

CONTEXT

In 2012, Colorado and Washington were the first states to legalize recreational marijuana. Both allowed local governments to further regulate the availability of marijuana facilities in their jurisdictions. As early adopters, these states are important quasi-natural experiments to examine local marijuana policy and policy change processes, including key stakeholders and arguments.

METHODS

We conducted a policy scan of county-level recreational marijuana ordinances and regulations in Colorado and Washington. Data collected included policy documents from counties in both states and newspaper articles. We used a mixed-methods approach to describe the types of county-level recreational marijuana policies enacted by April 1, 2019; identify key policy stakeholders involved in local policy debates; and explore arguments used in support or opposition of county policies. We also selected four counties that represent three county policy environments (all marijuana facility types allowed, some marijuana facility types allowed, all marijuana facility types prohibited) and described the policy changes within these counties since recreational marijuana was legalized.

FINDINGS

By April 1, 2019, Colorado counties were less likely than Washington counties to allow marijuana facilities-48.4% of Colorado counties prohibited recreational marijuana facilities in their jurisdiction compared to 23.1% of Washington counties. Since state legalization, several counties in both states have made substantial marijuana facility policy modifications, often preceded by information-seeking activities. Primary stakeholders involved in policy debates included elected officials, law enforcement, individual growers/farmers, marijuana business license applicants, parents, and residents. Proponents referenced local economic gain, reduced crime, and potential health benefits of marijuana as arguments in favor of permitting local facilities, whereas opponents pointed to economic loss, negative health and public health issues, public safety concerns, and existing federal law. Both sides referenced local public opinion data to support their position.

CONCLUSIONS

By early 2019, a patchwork of local marijuana policies was in place in Colorado and Washington. We identify key areas of policy and public health research needed to inform future local marijuana policy decisions, including the impact of legalization on public health outcomes (particularly for youth) and public safety.

Describing and evaluating healthcare priority setting practices at the county level in Kenya

BACKGROUND

Healthcare priority setting research has focused at the macro (national) and micro (patient level), while there is a dearth of literature on meso-level (subnational/regional) priority setting practices. In this study, we aimed to describe and evaluate healthcare priority setting practices at the county level in Kenya.

METHODS

We used a qualitative case study approach to examine the planning and budgeting processes in 2 counties in Kenya. We collected the data through in-depth interviews of senior managers, middle-level managers, frontline managers, and health partners (n = 23) and document reviews. We analyzed the data using a framework approach.

FINDINGS

The planning and budgeting processes in both counties were characterized by misalignment and the dominance of informal considerations in decision making. When evaluated against consequential conditions, efficiency and equity considerations were not incorporated in the planning and budgeting processes. Stakeholders were more satisfied and understood the planning process compared with the budgeting process. There was a lack of shifting of priorities and unsatisfactory implementation of decisions. Against procedural conditions, the planning process was more inclusive and transparent and stakeholders were more empowered compared with the budgeting process. There was ineffective use of data, lack of provisions for appeal and revisions, and limited mechanisms for incorporating community values in the planning and budgeting.

CONCLUSION

County governments can improve the planning and budgeting processes by aligning them, implementing a systematic priority setting process with explicit resource allocation criteria, and adhering to both consequential and procedural aspects of an ideal priority setting process.

The Use of Penalized Regression Analysis to Identify County-Level Demographic and Socioeconomic Variables Predictive of Increased COVID-19 Cumulative Case Rates in the State of Georgia

Systemic inequity concerning the social determinants of health has been known to affect morbidity and mortality for decades. Significant attention has focused on the individual-level demographic and co-morbid factors associated with rates and mortality of COVID-19. However, less attention has been given to the county-level social determinants of health that are the main drivers of health inequities. To identify the degree to which social determinants of health predict COVID-19 cumulative case rates at the county-level in Georgia, we performed a sequential, cross-sectional ecologic analysis using a diverse set of socioeconomic and demographic variables. Lasso regression was used to identify variables from collinear groups. Twelve variables correlated to cumulative case rates (for cases reported by 1 August 2020) with an adjusted r squared of 0.4525. As time progressed in the pandemic, correlation of demographic and socioeconomic factors to cumulative case rates increased, as did number of variables selected. Findings indicate the social determinants of health and demographic factors continue to predict case rates of COVID-19 at the county-level as the pandemic evolves. This research contributes to the growing body of evidence that health disparities continue to widen, disproportionality affecting vulnerable populations.

Impact of Hispanic ethnic concentration and socioeconomic status on obesity prevalence in Texas counties

The purpose of this study is to determine whether Hispanic ethnic concentration is associated with a higher prevalence of obesity and, if this relationship exists, whether it is affected by the socioeconomic environment. The study uses the Texas Behavioral Risk Factor Surveillance System (BRFSS) linked to 2000 census data to access the relationship between prevalence of obesity, Hispanic ethnic concentration, poverty and level of education at a county-level. The findings suggest that the association of Hispanic ethnic concentration and obesity varies by socioeconomic environment. Although little influence was observed for % poverty, the relationship between Hispanic ethnic concentration and obesity differed by county-level educational attainment. High proportion of residents with a bachelor's degree is associated with a low prevalence of obesity; counties with both high % Hispanic and high % with Bachelor's degrees had the lowest prevalence of obesity. Our results suggest that promoting and improving education, perhaps including training on healthful living, may serve as an effective means of curbing current obesity trends and associated health problems in Hispanic and possibly other ethnic communities.

Integrating sodium reduction strategies in the procurement process and contracting of food venues in the County of Los Angeles government, 2010-2012

Since sodium is ubiquitous in the food supply, recent approaches to sodium reduction have focused on increasing the availability of lower-sodium products through system-level and environmental changes. This article reviews integrated efforts by the Los Angeles County Sodium Reduction Initiative to implement these strategies at food venues in the County of Los Angeles government. The review used mixed methods, including a scan of the literature, key informant interviews, and lessons learned during 2010-2012 to assess program progress. Leveraging technical expertise and shared resources, the initiative strategically incorporated sodium reduction strategies into the overall work plan of a multipartnership food procurement program in Los Angeles County. To date, 3 County departments have incorporated new or updated nutrition requirements that included sodium limits and other strategies. The strategic coupling of sodium reduction to food procurement and general health promotion allowed for simultaneous advancement and acceleration of the County's sodium reduction agenda.

Local Social Vulnerability as a Predictor for Cancer-Related Mortality Among US Counties

Substantial gaps in national healthcare spending and disparities in cancer mortality rates are noted across counties in the US. In this cross-sectional analysis, we investigated whether differences in local county-level social vulnerability impacts cancer-related mortality. We linked county-level age-adjusted mortality rates (AAMR) from the Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research database, to county-level Social Vulnerability Index (SVI) from the CDC Agency for Toxic Substances and Disease Registry. SVI is a metric comprising 15 social factors including socioeconomic status, household composition and disability, minority status and language, and housing type and transportation. AAMRs were compared between least and most vulnerable counties using robust linear regression models. There were 4 107 273 deaths with an overall AAMR of 173 per 100 000 individuals. Highest AAMRs were noted in older adults, men, non-Hispanic Black individuals, and rural and Southern counties. Highest mortality risk increases between least and most vulnerable counties were noted in Southern and rural counties, individuals aged 45-65, and lung and colorectal cancers, suggesting that these groups may face highest risk for health inequity. These findings inform ongoing deliberations in public health policy at the state and federal level and encourage increased investment into socially disadvantaged counties.

Environmental Quality and Invasive Breast Cancer

Background: Breast cancer is a complex and multifactorial disease, and environmental factors have been suggested to increase its risk. However, prior research has largely focused on studying exposures to one factor/contaminant at a time, which does not reflect the real-world environment.Methods: Herein, we investigate associations between breast cancer and the environmental quality index (EQI), a comprehensive assessment of five domains of environmental quality (air, water, land, sociodemographic, and built environments) at the county level. Breast cancer diagnoses for North Carolina women were obtained from the North Carolina Central Cancer Registry (2009-2014) and the county of residence at the time of diagnosis was linked with the EQI. We evaluated the odds of localized, regional, or distant metastatic breast cancer in categories of environmental quality using women with carcinoma in situ as registry-based controls.Results: Overall environmental quality was generally not associated with invasive breast cancer; however, all breast cancer types tended to be inversely associated with land quality, particularly in more rural communities [distant metastatic breast cancer was 5%-8% more likely (OR, 1.08; 95% confidence interval, 1.02-1.14; P = 0.02) compared with carcinoma in situ].Conclusions: Cumulatively, our results suggest that some broad measures of environmental quality are associated with invasive breast cancer but that associations vary by environmental domain, cancer stage, subtype, and urbanicity.Impact: Our findings suggest that components of land quality (e.g., pesticide applications and animal facilities) warrant additional investigation in relation to invasive breast cancer.See all articles in this CEBP Focus section, "Environmental Carcinogenesis: Pathways to Prevention."

Prevalence of major external structural birth defects in Kiambu County, Kenya, 2014-2018

Introduction

major external structural birth defects are typical and have been associated with childhood morbidity, mortality and lifelong resource-intensive disabilities. These defects continue to occur; however, they are yet to be recognized as public health problems in Kenya. The objective of this study was to estimate the prevalence of major external structural birth defects in Kiambu County in Kenya, 2014-2018.

Methods

a cross-sectional study design was adopted; a retrospective review of medical records was conducted between 2014 and 2018 abstracting 873 birth defects. Following a predetermined inclusion criterion, a five-year prevalence numerator of 362 cases was determined, whereas, a five-year prevalence denominator of 299,854 cases of registered live-births was obtained from the birth registrar. Annual prevalence estimates of 29 sub-groups and 6 groups of these defects were calculated as the number of cases (numerator) divided by the number of live-births (denominator). Associated 95% binomial exact confidence intervals were also computed and expressed per 100,000 live-births.

Results

defects of the musculoskeletal system, the central nervous system, orofacial, genital organs, eye and anus were observed. Defects of the musculoskeletal system were the most prevalent, ranging from 22.98 (95% CI: 11.87-40.13) to 116.9 (95% CI: 92.98-145.08) per 100,000 live-births. Defects of the central nervous system followed ranging between 13.40 (95% CI: 5.39-27.61) and 32.79 (95% CI: 20.79-49.19) per 100,000 live-births.

Conclusion

despite musculoskeletal system defects being the most common group, hypospadias; a defect of the male genital organ was the most prevalent among the sub-group of these defects.

Cross-Jurisdictional Sharing for Emergency Management-Related Public Health: Exploring the Experiences of Tribes and Counties in California

Each American Indian tribe is unique in several ways, including in its relationships with local governments and risk for emergencies. Cross-jurisdictional sharing (CJS) arrangements are encouraged between tribes and counties for emergency management-related population health, but researchers have not yet explored CJS experiences of tribes and counties for emergency management. This investigation used collaboration theory and a CJS spectrum framework to assess the scope and prevalence of tribe-county CJS arrangements for emergency management in California as well as preconditions to CJS. Mixed-methods survey results indicate that tribes and counties have varied CJS arrangements, but many are informal or customary. Preconditions to CJS include tribe-county agreement about having CJS, views of the CJS relationship, barriers to CJS, and jurisdictional strengths and weaknesses in developing CJS arrangements. Areas for public health intervention include funding programs that build tribal capacity in emergency management, reduce cross-jurisdictional disagreement, and promote ongoing tribe-county relationships as a precursor to formal CJS arrangements. Study strengths, limitations, and future directions are also discussed.

COVID-19 Risk Perception and Support for COVID-19 Mitigation Measures among Local Government Officials in the U.S.: A Test of a Cultural Theory of Risk

This study relies on a cultural theory of risk to examine how cultural biases (hierarchy, individualism, egalitarianism, and fatalism) of local government officials affect their COVID-19 risk perception and support for COVID-19 mitigation measures. After controlling for partisanship, religiosity, and other factors, the analysis of survey data from county governments in the U.S. revealed that cultural biases matter. Officials with egalitarian and hierarchical cultural biases report higher support for adopting COVID-19 mitigation measures, while those with individualistic cultural biases report lower support. These findings highlight the need to understand cultural worldviews and develop cultural competencies necessary for governing traumatic events.

Micro-planning in a wide age range measles rubella (MR) campaign using mobile phone app, a case of Kenya, 2016

Introduction

A Measles rubella campaign that targeted 9 months to 14 year old children was conducted in all the 47 counties in Kenya between 16th and 24th of May 2016. Micro-planning using an android phone-based app was undertaken to map out the target population and logistics in all the counties 4 weeks to the campaign implementation instead of 6 months as per the WHO recommendation. The outcomes of the micro-planning exercise were a detailed micro-plan that served as a guide in ensuring that every eligible individual in the population was vaccinated with potent vaccine. A national Trainer of Trainers training was done to equip key officers with new knowledge and skills in developing micro-plans at all levels. The micro planning was done using a mobile phone app, the doforms that enabled data to be transmitted real time to the national level. The objective of the study was to establish whether use of mobile phone app would contribute to quality of sub national micro plans that can be used for national level planning and implementation of the campaign.

Methods

There were 9 data collection forms but only forms 1-7 were to be uploaded onto the app. Forms 8A and 9A were to be filled but were to remain at the implementation level for use intra campaign. The forms were coded; Form 1A&B, 2A, 3A, 4A, 5A, 6A, 7A, 8A and 9A The Village form (form 1A&B) captured information by household which included village names, name of head of household, cell phone contact of head of household, number of children aged 9 months to 14years in the household, possible barriers to reaching the children, appropriate vaccination strategy based on barriers identified and estimated or proposed number of teams and type. This was the main form and from this every other form picked the population figures to estimate other supplies and logistics. On advocacy, communication and social mobilization the information collected included mobile network coverage, public amenities such as churches, mosques and key partners at the local level. On human resource and cold chain supplies the information collected included number of health facilities by type, number of health workers by cadre in facilities within the village, number of vaccine carriers and icepacks by size, refrigerators and freezers. All these forms were to be uploaded onto the phone app. except form 8A, the individual team plan, which was to be used during implementation at the local level. Android phone application, doforms, was used to capture data. Training on micro planning, data entry and doforms app was conducted at National, County, Sub-county and ward levels using standardized guidelines. An interactive case study was used in all the trainings to facilitate understanding. The App was also available on Laptops through its provided web-application. The app allowed multiple users to log in concurrently. Feedback on all the variables were obtained from the team at the Ward level. The ward level team included education officers or teachers, village elders, community health workers and other community stakeholders. Only the Ward level was allowed to collect information on paper and that information was subsequently transferred to the phone-based app, doforms, by health information officers. The national, county and sub county were able to access their data from the app using a password provided by the administrator.

Results

Real time data was received from 46 of 47 counties. One county (Marsabit) did not participate in the micro plan process. Over 97% (283/290) of the sub counties responded and shared various information via the app. Different data forms had different completion rates. There was 100% completion rate for the data on villages and target population. Much valuable information was shared but there was no time for the national and county level to interrogate and harmonize for proper implementation. The information captured during the campaign can be used for routine immunization and other community based interventions. Electronic data collection not only provided the number of children but provided the locations also where these children could be found.

Conclusion

Despite the limitations of time to harmonize the micro plans with the national plan, the micro planning process was a great success with 46/47 counties responding through the mobile phone app. Not only did it provide the numbers of the target children, it further provided the places where these children could be found. There was timely data transfer, data integrity, tracking, real time data visualization reporting and analysis. The app enabled real time feedback to national focal point by data entry clerks as well as enabling trouble shooting by the administrator. This ensured campaign planning was done from the lowest level to the national level.

Temporal and Spatial Variations in the Twinning Rate in Norway

Strong geographical variations have been noted in the twinning rate (TWR). In general, the rate is high among people of African origin, intermediate among Europeans, and low among most Asiatic populations. In Europe, there tends to be a south-north cline, with a progressive increase in the TWR from south to north and a minimum around the Basque provinces. The highest TWRs in Europe have been found among the Nordic populations. Furthermore, within larger populations, small isolated subpopulations have been identified to have extreme, mainly high, TWRs. In the study of the temporal variation of the TWR in Norway, we consider the period from 1900 to 2014. The regional variation of the TWR in Norway is analyzed for the different counties for two periods, 1916-1926 and 1960-1988. Heterogeneity between the regional TWRs in Norway during 1916-1926 was found, but the goodness of fit for the alternative spatial models was only slight. The optimal regression model for the TWR in Norway has the longitude and its square as regressors. According to this model, the spatial variation is distributed in a west-east direction. For 1960-1988, no significant regional variation was observed. One may expect that the environmental and genetic differences between the counties in Norway have disappeared and that the regional TWRs have converged towards a common low level.

Multiscale dimensions of county-level disparities in opioid use disorder rates among older Medicare beneficiaries

Background

Opioid use disorder (OUD) among older adults (age ≥ 65) is a growing yet underexplored public health concern and previous research has mainly assumed that the spatial process underlying geographic patterns of population health outcomes is constant across space. This study is among the first to apply a local modeling perspective to examine the geographic disparity in county-level OUD rates among older Medicare beneficiaries and the spatial non-stationarity in the relationships between determinants and OUD rates.

Methods

Data are from a variety of national sources including the Centers for Medicare & Medicaid Services beneficiary-level data from 2020 aggregated to the county-level and county-equivalents, and the 2016-2020 American Community Survey (ACS) 5-year estimates for 3,108 contiguous US counties. We use multiscale geographically weighted regression to investigate three dimensions of spatial process, namely "level of influence" (the percentage of older Medicare beneficiaries affected by a certain determinant), "scalability" (the spatial process of a determinant as global, regional, or local), and "specificity" (the determinant that has the strongest association with the OUD rate).

Results

The results indicate great spatial heterogeneity in the distribution of OUD rates. Beneficiaries' characteristics, including the average age, racial/ethnic composition, and the average hierarchical condition categories (HCC) score, play important roles in shaping OUD rates as they are identified as primary influencers (impacting more than 50% of the population) and the most dominant determinants in US counties. Moreover, the percentage of non-Hispanic white beneficiaries, average number of mental health conditions, and the average HCC score demonstrate spatial non-stationarity in their associations with the OUD rates, suggesting that these variables are more important in some counties than others.

Conclusions

Our findings highlight the importance of a local perspective in addressing the geographic disparity in OUD rates among older adults. Interventions that aim to reduce OUD rates in US counties may adopt a place-based approach, which could consider the local needs and differential scales of spatial process.

Socioeconomic factors and bacillary dysentery risk in Jiangsu Province, China: a spatial investigation using Bayesian hierarchical models

Bacillary dysentery (BD) is an acute diarrheal disease prevalent in areas affected by socioeconomic disparities. We investigated BD risk and its associations with socioeconomic factors at the county-level in Jiangsu province, China using epidemiological and socioeconomic data from 2011-2014. We fitted four Bayesian hierarchical models with various prior specifications for random effects. As all model comparison criteria values were similar, we presented results from a reparameterized Besag-York-Mollié model, which addressed issues with the identifiability of variance captured by spatial and independent effects. Our model adjusted for year and socioeconomic status showed 18-65% decreased BD risk compared to 2011. We found a high relative risk in the northwestern and southwestern counties. Increasing the percentage of rural households, rural income per capita, health institutions per capita, or hospital beds per capita decreases the relative risk of BD, respectively. Our findings can be used to improve infectious diarrhea surveillance and enhance existing public health interventions.

A protracted cholera outbreak among residents in an urban setting, Nairobi county, Kenya, 2015

Introduction

in 2015, a cholera outbreak was confirmed in Nairobi county, Kenya, which we investigated to identify risk factors for infection and recommend control measures.

Methods

we analyzed national cholera surveillance data to describe epidemiological patterns and carried out a case-control study to find reasons for the Nairobi county outbreak. Suspected cholera cases were Nairobi residents aged >2 years with acute watery diarrhea (>4 stools/≤12 hours) and illness onset 1-14 May 2015. Confirmed cases had Vibrio cholerae isolated from stool. Case-patients were frequency-matched to persons without diarrhea (1:2 by age group, residence), interviewed using standardized questionaires. Logistic regression identified factors associated with case status. Household water was analyzed for fecal coliforms and Escherichia coli.

Results

during December 2014-June 2015, 4,218 cholera cases including 282 (6.7%) confirmed cases and 79 deaths (case-fatality rate [CFR] 1.9%) were reported from 14 of 47 Kenyan counties. Nairobi county reported 781 (19.0 %) cases (attack rate, 18/100,000 persons), including 607 (78%) hospitalisations, 20 deaths (CFR 2.6%) and 55 laboratory-confirmed cases (7.0%). Seven (70%) of 10 water samples from communal water points had coliforms; one had Escherichia coli. Factors associated with cholera in Nairobi were drinking untreated water (adjusted odds ratio [aOR] 6.5, 95% confidence interval [CI] 2.3-18.8), lacking health education (aOR 2.4, CI 1.1-7.9) and eating food outside home (aOR 2.4, 95% CI 1.2-5.7).

Conclusion

we recommend safe water, health education, avoiding eating foods prepared outside home and improved sanitation in Nairobi county. Adherence to these practices could have prevented this protacted cholera outbreak.

Practice and Enlightenment of Chronic Disease Management at the County Level in China from the Perspective of Professional Integration: A Qualitative Case Study of Youxi County, Fujian Province

Background

It is currently the most cost-effective management model to have multiple professionals from relevant institutions collaborate so as to provide integrated chronic disease management services. The "classified, color-coded, hierarchical and regionalized" chronic disease management model in Youxi County, Fujian Province is a typical case in China. However, related research is limited. This paper aims to analyze the practice measures and lessons learned in Youxi County, focusing on the professional integration of service providers.

Methods

From January to March 2021, interviews with 15 key informants in Youxi County were conducted to collect qualitative data, which was analyzed by the thematic framework method as well as the policy data, using the professional integration dimension in the evaluation framework of the integrated healthcare system.

Results

A series of measures were taken, such as improving the professional division and collaboration mechanism, establishing the incentive and restraint mechanism geared toward chronic disease management, formulating norms and standards of chronic disease management for patients with different color labels, and promoting the compatibility of inter-professional value and culture under the governmental institutional supply and the organizational support of the tight county healthcare alliance in Youxi County, to prompt professionals of different levels and types to collaborate in order to provide integrated chronic disease management services. However, some problems remained, such as limited capacity of primary health care, the relatively narrow range and weak effect of the incentive and restraint mechanism, inadequate implementation of the norms and standards, and so forth.

Conclusions

Our findings provide reference for other regions in China and other low- and middle-income countries in exploring the integrated chronic disease management model. Long-term follow-up surveys and mixed research designs are required in the future to enrich relevant evidence.

Strengthening health financing at sub-national level in Kenya: a stakeholder and needs mapping through a mixed methods approach

Introduction

health financing aims to ensure that the overall goal of the health system is attained. Countries with decentralised healthcare systems such as Kenya, face further challenges due to limited public financial management capacity within sub-national governments. While partner support has proved impactful in addressing these challenges, there is a paucity of evidence on the nature and distribution of the support in Kenya. This study sought to examine the current technical support and health financing support offered by partners across the 47 counties in Kenya.

Methods

the study used a descriptive cross-sectional design with a mixed methods approach. Quantitative data were collected from organisation representatives using semi-structured questionnaires and analysed using Microsoft Excel. Qualitative data were collected through key informants and in-depth interviews involving county Department of Health officials in 15 counties in Kenya. Interview recordings were transcribed and thematically analysed using NVIVO version 14.

Results

twenty (20) organisations reportedly provided health financing support to counties with planning, budgeting and health financing advocacy being the most supported work streams by partners. While each county had more than one partner supporting health financing activities, the western counties had more partners compared to other regions of Kenya. Whereas partner support was well acknowledged at the county level, there was a lack of coordination and alignment of partner activities with county priorities.

Conclusion

these findings highlight the essential need for national governments to ensure effective coordination of the technical assistance provided by partners to subnational levels and to ensure equitable distribution of support and alignment with county health priorities and needs.

Injuries treated in hospital among urban and rural inhabitants of eastern Poland

INTRODUCTION AND OBJECTIVE

Injuries are a serious medical and social problem, especially when accompanied by distant or deferred effects, often causing serious dysfunctions and permanent disability for life. The study aimed at presenting the incidence of injuries of urban and rural population treated in a district hospital in eastern Poland.

MATERIAL AND METHODS

The study was carried out in the Independent Public Health Care Institution in Kraśnik in 2011 among patients hospitalized in the Department of Trauma Surgery and Orthopedic Unit who sustained injuries. Medical records of 795 patients - 326 women and 469 men, aged 10-99 years, were analyzed.

RESULTS

During the period considered among those hospitalized due to injuries, men (59%), those aged 50-59 years (19.0%), and living in rural areas (72.7%) predominated. Injuries most commonly affected the head (18.87%), elbow and forearm (16.86%), knee and lower leg (16.60%), and the hip and thigh (13.96%). Average hospital stay was 5.65 days and was the longest for hip and thigh injuries (11.86 days).

CONCLUSIONS

Injuries occurred most frequently in the population of patients living in rural areas, often among men, usually on weekdays and in the morning.