Socioeconomic impacts of COVID-19 pandemic on foodborne illnesses in the United States.

Foodborne diseases continue to impact human health and the economy. The COVID-19 pandemic has dramatically affected the food system from production to consumption. This project aims to determine the impact of the COVID-19 pandemic on the spread of foodborne diseases and the factors that may have contributed, including environmental, behavioral, political, and socioeconomic. Data for this study were collected from The Foodborne Diseases Active Surveillance Network (FoodNet) for 2015-2020. FoodNet personnel located at state health departments regularly contact the clinical laboratories in Connecticut (CT), Georgia (GA), Maryland (MD), Minnesota (MN), New Mexico (NM), Oregon (OR), Tennessee (TN), and selected counties in California (CA), Colorado (CO), and New York (NY). Data were analyzed using SAS to determine the changes in rates of foodborne pathogens reported in FoodNet before and during the COVID-19 pandemic in the ten reporting states. Results of the study showed a significant decline in the incidences of foodborne diseases ranging between 25% and 60%. A geographical variation was also observed between California and states with the highest decline rate of foodborne illnesses. Policies and restrictions, in addition to environmental and behavioral changes during the COVID-19 pandemic, may have reduced rates of foodborne diseases.

COVID-19 Progression: A County-Level Analysis of Vaccination and Case Fatality in Mississippi, USA.

The COVID-19 pandemic has created a severe upheaval in the U.S., with a particular burden on the state of Mississippi, which already has an exhausted healthcare burden. The main objectives of this study are: (1) to analyze the county-level COVID-19 cases, deaths, and vaccine distribution and (2) to determine the correlation between various social determinants of health (SDOH) and COVID-19 vaccination coverage. We analyzed COVID-19-associated data and county-level SDOH factors in 82 counties of Mississippi. The cumulative COVID-19 and socio-demographic data variables were grouped into feature and target variables. The statistical and exploratory data analysis (EDA) was conducted using Python 3.8.5. The correlation between the target and feature variables was performed by Pearson Correlation analysis. The heat Map Correlation Matrix was visually presented to illustrate the correlation between each pair of features and each target variable. Results indicated that people of Asian descent had the highest vaccination coverage of 77% fully vaccinated compared to 52%, 46%, 42% and 25% for African Americans, Whites, Hispanics, and American Indians/Alaska Natives, respectively. The county-level vaccination rate was significantly higher among the minority populations than the White population. It was observed that COVID-19 cases and deaths were positively correlated with per capita income and negatively correlated with the percentage of persons without a high school diploma (age 25+). This study strongly demonstrates that different SDOH factors influence the outcome of the COVID-19 vaccination rate, which also affects the total number of COVID-19 cases and deaths. Vaccine promotion should be given to all populations regardless of race and ethnicity to achieve uniform acceptance. Therefore, statewide policy recommendations focusing on specific community needs should help achieve health equity in COVID-19 vaccination management.

COVID-19 Incidence and Death Rates in the Southern Region of the United States: A Racial and Ethnic Association.

The SARS-CoV-2 virus responsible for the COVID-19 pandemic continues to spread worldwide, with over half a billion cases linked to over 6 million deaths globally. COVID-19 has impacted populations unequally based on income, age, race, sex, and geographical location. This study aimed to characterize COVID-19 incidence and death rate trends in six states of the southern region of the USA and to understand the demographic and racial differences in its incidence and death rates. Data for the study were collected from the COVID-19 Data tracker of the Centers for Disease Control and Prevention for the following southern states: Alabama (AL), Florida (FL), Georgia (GA), Louisiana (LA), Mississippi (MS), and Tennessee (TN). The results showed a significant geographical variation in the COVID-19 cases and related deaths. Significant variations in COVID-19 cases and death rates were observed among different races and ethnic groups. The highest number of COVID-19 cases were observed among the Hispanic and Black populations, and the highest death rates were found among non-Hispanic Blacks and Whites. The southern states included in this paper showed a high number of COVID-19 cases and high death rates during the study period. These increased rates may result from the low socioeconomic status and large minority populations.

Trends of Foodborne Diseases in Mississippi: Association with Racial and Economic Disparities.

BACKGROUND: Foodborne diseases are a major source of concern in USA. These diseases are a burden on public health and significantly contribute to the cost of health care. There is an urgent need to understand the contributing factors for such outbreaks, especially in Mississippi (MS), an agricultural state with low socioeconomic status. METHODS: Secondary data for the current study were obtained from the Mississippi State Department of Health (MSDH) Epidemiology department for the study period 2010-2018. Data were for individuals with reported foodborne diseases cases. The data were analyzed to determine the pathogens' trend over time, the highest contributing pathogens to foodborne diseases, the significant geographical variation, and any significant differences in rates based on demographic variables. RESULTS: Salmonella was the highest contributing pathogen to foodborne disease in MS. The study showed a seasonal variation in the trends of pathogens and a geographical variation, and no racial differences in the incidents of the foodborne diseases was observed. CONCLUSIONS: Incidence rates of foodborne illness remain high in the state of Mississippi. A better understanding of high levels of foodborne infections caused by Salmonella, Shigella, and Campylobacter resulting from cultural food handling practices or socioeconomic factors will allow to provide guidelines and food safety preventive measures.

Using multi theory model (MTM) of health behavior change to explain intention for initiation and sustenance of the consumption of fruits and vegetables among African American men from barbershops in Mississippi.

Background: African American men have poorer health outcomes compared to their white counterparts despite medical advancements and early detection of diseases. The purpose of this study was to determine to what extent the constructs of the multi theory model (MTM) explain the intention for initiation and sustenance of the consumption of fruits and vegetables among African American adult men in Mississippi. Methods: Using a cross-sectional design a valid and reliable paper survey was administered during November and December of 2019. The target population for the study consisted of African American adult men (18 or older) that had not consumed recommended levels of fruits and vegetables within 24 hours of taking the questionnaire. A convenience quota sample of African American men from select barbershops in Jackson, Mississippi, were asked to complete the 40-item questionnaire on preventive health screening behavior (n=134). Results: The mean total number of fruits and vegetables consumed by participants within 24hours of the taking the survey was 1.63 (SD =1.47). The mean intention to initiate consuming 5or more cups of fruits and vegetables per day score was 2.13 (SD=1.17) as measured on a 5-point scale (0-4). Behavioral confidence (ß = 0.495, P<0.0001), and changes in physical environment(ß = 0.230, P<0.0001) accounted for 40.8% of the variance in predicting the intention to initiate behavioral change regarding the daily consumption of fruits and vegetables. Practice for change (ß = 0.462, P<0.001) and emotional transformation (ß = 0.215, P<0.0001) accounted for 37.5% of the variance in the intention to sustain fruits and vegetables consumption behavior. Conclusion: Based on data found in the study, MTM appears to predict the intention to initiate and sustain fruit and vegetable intake of African American men. Further research studies of suitable interventions to target African American men are needed.

Exploring Unconventional Risk-Factors for Cardiovascular Diseases: Has Opioid Therapy Been Overlooked?

Approximately 2150 adults die every day in the U.S. from Cardiovascular Diseases (CVD) and another 115 deaths are attributed to opioid-related causes. Studies have found conflicting results on the relationship between opioid therapy and the development of cardiovascular diseases. This study examined whether an association exists between the use of prescription opioid medicines and cardiovascular diseases, using secondary data from the National Hospital Ambulatory Medical Care Survey (NAMCS) 2015 survey. Of the 1829 patients, 1147 (63%) were male, 1762 (98%) above 45 years of age, and 54% were overweight. The rate of cardiovascular diseases was higher among women [(p < 0.001), 95% CI: 0.40-0.51]. The covariates were age, race/ethnicity, sex, diabetes mellitus, hyperlipidemia, and hypertension; and were adjusted. Diabetes mellitus, hyperlipidemia, and hypertension were significant predictors of CVD [(p < 0.001, 95% CI: 0.57-0.78); (p < 0.001, 95% CI: 0.34-0.44); (p < 0.001, 95% CI: 0.49-0.59)]. There was no significant association between prescription opioid medication use and coronary artery disease [first opioid group p = 0.34, Prevalence Odds Ratio (POR): 1.39, 95% CI: 0.71-2.75; second opioid group: p = 0.59, POR: 1.20, 95% CI: 0.61-2.37, and third opioid group: p = 0.62, POR: 0.85, 95% CI: 0.45-1.6]. The results of this study further accentuate the conflicting results in literature. Further research is recommended, with a focus on those geographical areas where high prevalence of cardiovascular diseases exists.

Quantitative Risk Assessment Model of Human Salmonellosis Resulting from Consumption of Broiler Chicken.

(1) Background: Salmonella infections are a major cause of illnesses in the United States. Each year around 450 people die from the disease and more than 23,000 people are hospitalized. Salmonella outbreaks are commonly associated with eggs, meat and poultry. In this study, a quantitative risk assessment model (QRAM) was developed to determine Salmonella infections in broiler chicken. (2) Methods: Data of positive Salmonella infections were obtained from the United States Department of Agriculture (USDA) and the Centers for Disease Control and Prevention (CDC) Foodborne Disease Outbreak Surveillance System, in addition to published literature. The Decision Tools @RISK add-in software was used for various analyses and to develop the QRAM. The farm-to-fork pathway was modeled as a series of unit operations and associated pathogen events that included initial contamination at the broiler house (node 1), contamination at the slaughter house (node 2), contamination at retail (node 3), cross-contamination during serving and cooking (node 4), and finally the dose⁻response model after consumption. (3) Results: QRAM of Salmonella infections from broiler meat showed highest contribution of infection from the retail node (33.5%). (4) Conclusions: This QRAM that predicts the risk of Salmonella infections could be used as a guiding tool to manage the Salmonella control programs.

The recent outbreaks and reemergence of poliovirus in war and conflict-affected areas.

BACKGROUND: Poliomyelitis is a highly infectious disease caused by poliovirus, which becomes difficult to manage/eradicate in politically unstable areas. The objectives of this study were to determine the movement and management of such polio outbreaks in endemic countries and countries with reoccurring cases of polio and to determine the effect of political instability on polio eradication. METHODS: In this study, the extent of polio outbreaks was examined and modeled using statistical methodologies and mapped with GIS software. Data on polio cases and immunization were collected for countries with polio cases for the period 2011 to 2014. Weekly data from the Global Polio Eradication Initiative were collected for selected countries. The recent virus origin and current movement was mapped using GIS. Correlations between immunization rates, the Global Peace Index (GPI), and other indicators of a country's political stability with polio outbreaks were determined. Data were analyzed using SAS 9.4 and ArcGIS 10. RESULTS: For several reasons, Pakistan remains highly vulnerable to new incidences of polio (306 cases in 2014). Overall immunization rates showed a steady decline over time in selected countries. Countries with polio cases were shown to have high rates of infant mortality, and their GPI ranked between 2.0 and 3.3; displaced populations, level of violent crime rating, and political instability also were ranked high for several countries. CONCLUSION: Polio was shown to be high in areas with increased conflict and instability. Displaced populations living in hard-to-reach areas may lack access to proper vaccination and health care. Wars and conflict have also resulted in the reemergence of polio in otherwise polio-free countries.

Salmonella infections modelling in Mississippi using neural network and geographical information system (GIS).

OBJECTIVES: Mississippi (MS) is one of the southern states with high rates of foodborne infections. The objectives of this paper are to determine the extent of Salmonella and Escherichia coli infections in MS, and determine the Salmonella infections correlation with socioeconomic status using geographical information system (GIS) and neural network models. METHODS: In this study, the relevant updated data of foodborne illness for southern states, from 2002 to 2011, were collected and used in the GIS and neural networks models. Data were collected from the Centers for Disease Control and Prevention (CDC), MS state Department of Health and the other states department of health. The correlation between low socioeconomic status and Salmonella infections were determined using models created by several software packages, including SAS, ArcGIS @RISK and NeuroShell. RESULTS: Results of this study showed a significant increase in Salmonella outbreaks in MS during the study period, with highest rates in 2011 (47.84 ± 24.41 cases/100,000; p<0.001). MS had the highest rates of Salmonella outbreaks compared with other states (36 ± 6.29 cases/100,000; p<0.001). Regional and district variations in the rates were also observed. GIS maps of Salmonella outbreaks in MS in 2010 and 2011 showed the districts with higher rates of Salmonella. Regression analysis and neural network models showed a moderate correlation between cases of Salmonella infections and low socioeconomic factors. Poverty was shown to have a negative correlation with Salmonella outbreaks (R(2)=0.152, p<0.05). CONCLUSIONS: Geographic location besides socioeconomic status may contribute to the high rates of Salmonella outbreaks in MS. Understanding the geographical and economic relationship with infectious diseases will help to determine effective methods to reduce outbreaks within low socioeconomic status communities.

Trends in infant mortality in United States: a brief study of the Southeastern states from 2005-2009.

While overall infant mortality rates have declined over the past several decades, the Southeastern states have remained the leading states in high infant death in the United States. In this study, we studied the differences in infant mortality in the southeastern United States from 2005 through 2009 according to mother's characteristics (age of mother, marital status, maternal race, maternal education), birth characteristics (month when maternal prenatal care began, birth weight), and infant's characteristics (age of infant at death). This paper illustrates the significance level of each characteristic of mothers and infants, as well as socioeconomic factors that contribute to significant infant mortality that impacts subgroups within the US population. Descriptive statistics and analysis of variance studies were performed and presented. Statistical analysis of the contribution of causes of infant death to infant mortality at the national and state level was elaborated. Data suggest that mothers with no prenatal care had a very high overall infant death rate (5281.83 and 4262.16 deaths per 100,000 births in Mississippi and Louisiana, respectively, whereas the US average was 3074.82 deaths (p < 0.01)). It is suggested that better education and living quality should be available and improved for the residents in Alabama, Louisiana, and Mississippi.

Effects of climate change on Salmonella infections.

BACKGROUND: Climate change and global warming have been reported to increase spread of foodborne pathogens. To understand these effects on Salmonella infections, modeling approaches such as regression analysis and neural network (NN) were used. METHODS: Monthly data for Salmonella outbreaks in Mississippi (MS), Tennessee (TN), and Alabama (AL) were analyzed from 2002 to 2011 using analysis of variance and time series analysis. Meteorological data were collected and the correlation with salmonellosis was examined using regression analysis and NN. RESULTS: A seasonal trend in Salmonella infections was observed (p<0.001). Strong positive correlation was found between high temperature and Salmonella infections in MS and for the combined states (MS, TN, AL) models (R(2)=0.554; R(2)=0.415, respectively). NN models showed a strong effect of rise in temperature on the Salmonella outbreaks. In this study, an increase of 1°F was shown to result in four cases increase of Salmonella in MS. However, no correlation between monthly average precipitation rate and Salmonella infections was observed. CONCLUSION: There is consistent evidence that gastrointestinal infection with bacterial pathogens is positively correlated with ambient temperature, as warmer temperatures enable more rapid replication. Warming trends in the United States and specifically in the southern states may increase rates of Salmonella infections.

Relationships between obesity and cardiovascular diseases in four southern states and Colorado.

Obesity is among the leading causes of elevated cardiovascular disease (CVD) mortality and morbidity. In the present study, the associations between the increase in body mass index (BMI) and the increase rates of CVD and high blood pressure (HBP) in the states of Mississippi, Alabama, Louisiana, Tennessee, and Colorado are examined using regression analysis and by means of neural network models for obesity and HBP. Data from Behavioral Risk Factor Surveillance System were obtained and analyzed for obesity rates, percent of myocardial infarction, stroke, and HBP from 2005-2009. Results of this study showed a low association between obesity and myocardial infarction rates (R2=0.067); a moderate association with stroke rates ((R2=0.462); and a strong association with HBP rates ((R2=0.811). The highest rates of obesity, CVD, and HBP were found in Mississippi, while Colorado had the lowest rates. Maintaining healthy weight helps reduce the risks of developing CVD.

HIV and tuberculosis trends in the United States and select Sub-Saharan Africa countries.

Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) are two catastrophic diseases affecting millions of people worldwide every year; and are considered to be pandemic by the World Health Organization. This study aims to compare the recent trends in TB and HIV in the United States and Sub-Saharan African Countries. Data (incidence, prevalence and death rates of HIV and TB) for the United States, Cameroon, Nigeria, and South Africa were collected from The Joint United Nations Programme for HIV/AIDS (UNAIDS), US Census Bureau and World Health Organization (WHO) databases and analyzed using Statistical Analysis Software (SAS v 9.1). Analysis of Variance (ANOVA) was performed to compare the variables of interest between the countries and across time. Results showed that percent rates of TB cases, TB deaths, HIV cases and HIV deaths were significantly different (P<0.001) among these countries from 1993 to 2006. South Africa had the highest rates of HIV and TB; while US had the lowest rates of both diseases. Tuberculosis and HIV rates for Cameroon and Nigeria were significantly higher when compared to the United States, but were significantly lower when compared to South Africa (P<0.001). There were significant differences (P<0.001) in the prevalence of TB and HIV between the United States and the Sub-Saharan African countries, as well as differences within the Sub-Saharan African countries from 1993 to 2006. More analysis needs to be carried out in order to determine the prevalence and incidence of HIV and TB among multiple variables like gender, race, sexual orientation and age to get a comprehensive picture of the trends of HIV and TB.

Effects of socioeconomic factors on obesity rates in four southern states and Colorado.

OBJECTIVE: To examine the association between the increase in body mass index (BMI) and socioeconomic factors (eg, income level, % below poverty line, unemployment rates and persons receiving food stamps) in Mississippi, Alabama, Louisiana, Tennessee and Colorado. DESIGN: Data from Behavioral Risk Factor Surveillance System, United States Department of Agriculture and the United States Department of Labor/Bureau of Labor were obtained and analyzed for the years 1995-2008. RESULTS: Results from this study showed a strong association between obesity and the tested variables (R2 = .767). Factors more closely related with obesity were: income below poverty level; receipt of food stamps; unemployment; and general income level. The coefficient of determination for these variables were 0.438, 0.427, 0.103 and 0.018, respectively. The highest rate of obesity was found in Mississippi (26.5% +/- 4.13%) followed by Alabama (25.18% +/- 4.41%), while Colorado had the lowest rate of obesity (15.4% +/- 2.63%). By ethnicity, African Americans had the highest rate of obesity (32.64 +/- 5.99%). CONCLUSION: We found a significant effect of consumption of low-quality food, due to economic factors, on increased BMI. Besides physical activity, the quality and the quantity of food are important factors that contribute to obesity rates.