Disparities in SARS-CoV-2 seroprevalence among individuals presenting for care in central North Carolina over a six-month period.

Background: Robust community-level SARS-CoV-2 prevalence estimates have been difficult to obtain in the American South and outside of major metropolitan areas. Furthermore, though some previous studies have investigated the association of demographic factors such as race with SARS-CoV-2 exposure risk, fewer have correlated exposure risk to surrogates for socioeconomic status such as health insurance coverage. Methods: We used a highly specific serological assay utilizing the receptor binding domain of the SARS-CoV-2 spike-protein to identify SARS-CoV-2 antibodies in remnant blood samples collected by the University of North Carolina Health system. We estimated the prevalence of SARS-CoV-2 in this cohort with Bayesian regression, as well as the association of critical demographic factors with higher prevalence odds. Findings: Between April 21st and October 3rd of 2020, a total of 9,624 unique samples were collected from clinical sites in central NC and we observed a seroprevalence increase from 2·9 (1·7, 4·3) to 9·1 (7·2, 11·1) over the study period. Individuals who identified as Latinx were associated with the highest odds ratio of SARS-CoV-2 exposure at 7·77 overall (5·20, 12·10). Increased odds were also observed among Black individuals and individuals without public or private health insurance. Interpretation: Our data suggests that for this care-accessing cohort, SARS-CoV-2 seroprevalence was significantly higher than cumulative total cases reported for the study geographical area six months into the COVID-19 pandemic in North Carolina. The increased odds of seropositivity by ethnoracial grouping as well as health insurance highlights the urgent and ongoing need to address underlying health and social disparities in these populations.

SARS-CoV-2 testing in North Carolina: Racial, ethnic, and geographic disparities.

SARS-CoV-2 testing data in North Carolina during the first three months of the state's COVID-19 pandemic were analyzed to determine if there were disparities among intersecting axes of identity including race, Latinx ethnicity, age, urban-rural residence, and residence in a medically underserved area. Demographic and residential data were used to reconstruct patterns of testing metrics (including tests per capita, positive tests per capita, and test positivity rate which is an indicator of sufficient testing) across race-ethnicity groups and urban-rural populations separately. Across the entire sample, 13.1% (38,750 of 295,642) of tests were positive. Within racial-ethnic groups, 11.5% of all tests were positive among non-Latinx (NL) Whites, 22.0% for NL Blacks, and 66.5% for people of Latinx ethnicity. The test positivity rate was higher among people living in rural areas across all racial-ethnic groups. These results suggest that in the first three months of the COVID-19 pandemic, access to COVID-19 testing in North Carolina was not evenly distributed across racial-ethnic groups, especially in Latinx, NL Black and other historically marginalized populations, and further disparities existed within these groups by gender, age, urban-rural status, and residence in a medically underserved area.

The Burden of Malaria in the Democratic Republic of the Congo.

Despite evidence that older children and adolescents bear the highest burden of malaria, large malaria surveys focus on younger children. We used polymerase chain reaction data from the 2013-2014 Demographic and Health Survey in the Democratic Republic of Congo (including children aged <5 years and adults aged ≥15 years) and a longitudinal study in Kinshasa Province (participants aged 6 months to 98 years) to estimate malaria prevalence across age strata. We fit linear models and estimated prevalences for each age category; adolescents aged 10-14 years had the highest prevalence. We estimate approximately 26 million polymerase chain reaction-detectable infections nationally. Adolescents and older children should be included in surveillance studies.

Case reduction and cost-effectiveness of the RTS,S/AS01 malaria vaccine alongside bed nets in Lilongwe, Malawi.

BACKGROUND: RTS,S/AS01, the most advanced vaccine against malaria, is now undergoing pilot implementation in Malawi, Ghana, and Kenya where an estimated 360,000 children will be vaccinated each year. In this study we evaluate RTS,S/AS01 alongside bed net use and estimate cost-effectiveness. METHODS: RTS,S/AS01 phase III trial and bed net prevalence data were used to determine the effect of vaccination in the urban/periurban and rural areas of Lilongwe, Malawi. Cost data were used to calculate the cost-effectiveness of various interventions over three years. FINDINGS: Since bed nets reduce malaria incidence and homogeneous vaccine efficacy was assumed, participants without bed nets received greater relative benefit from vaccination with RTS,S/AS01 than participants with bed nets. Similarly, since malaria incidence in rural Lilongwe is higher than in urban Lilongwe, the impact and cost-effectiveness of vaccine interventions is increased in rural areas. In rural Lilongwe, we estimated that vaccinating one child without a bed net would prevent 2·59 (1·62 to 3·38) cases of malaria over three years, corresponding to a cost of $10·08 (7·71 to 16·13) per case averted. Alternatively, vaccinating one child with a bed net would prevent 1·59 (0·87 to 2·57) cases, corresponding to $16·43 (10·16 to 30·06) per case averted. Providing RTS,S/AS01 to 30,000 children in rural Lilongwe was estimated to cost $782,400 and to prevent 58,611 (35,778 to 82,932) cases of malaria over a three-year period. Joint interventions providing both vaccination and bed nets (to those without them) were estimated to prevent additional cases of malaria and to be similarly cost-effective, compared to vaccine-only interventions. INTERPRETATION: To maximize malaria prevention, vaccination and bed net distribution programs could be integrated. FUNDING: Impacts of Environment, Host Genetics and Antigen Diversity on Malaria Vaccine Efficacy (1R01AI137410-01).

Hospital surge capacity for an influenza pandemic in the triangle region of North Carolina.

This research investigates the geographic aspects of health care delivery in the event of a sudden increase in the need for care. We constructed an integrated disease outbreak and surge capacity model to evaluate the ability of a region's healthcare system to provide care in the event of a pandemic. In a case study, we implement the model to investigate how an influenza pandemic similar to the 1918 Spanish Flu pandemic would affect the population of the Raleigh-Durham-Chapel Hill metropolitan statistical area and the ability of the region's hospital system to respond to such an event. Under varying scenarios for hospital capacity, we found that the population needing care would overwhelm the system's ability to provide care in the case study. Our model is presented as a framework that can be augmented and expanded to suit the needs of the particular event and healthcare system or services required. By integrating concepts and models from epidemiology, geography, and health care services research, we provide a valuable tool for potential use in disaster planning, hospital system evaluation, and pandemic preparedness.

Where Are Adults Active? An Examination of Physical Activity Locations Using GPS in Five US Cities.

Increasing physical activity (PA) at the population level requires appropriately targeting intervention development. Identifying the locations in which participants with various sociodemographic, body weight, and geographic characteristics tend to engage in varying intensities of PA as well as locations these populations underutilize for PA may facilitate this process. A visual location-coding protocol was developed and implemented in Google Fusion Tables and Maps using data from participants (N = 223, age 18-85) in five states. Participants concurrently wore ActiGraph GT1M accelerometers and Qstarz BT-Q1000X GPS units for 3 weeks to identify locations of moderate-to-vigorous (MVPA) or vigorous (VPA) bouts. Cochran-Mantel-Haenzel general association tests examined usage differences by participant characteristics (sex, age, race/ethnicity, education, body mass index (BMI), and recruitment city). Homes and roads encompassed >40% of bout-based PA minutes regardless of PA intensity. Fitness facilities and schools were important for VPA (19 and 12% of bout minutes). Parks were used for 13% of MVPA bout minutes but only 4% of VPA bout minutes. Hispanics, those without a college degree, and overweight/obese participants frequently completed MVPA bouts at home. Older adults often used roads for MVPA bouts. Hispanics, those with ≤high school education, and healthy/overweight participants frequently had MVPA bouts in parks. Applying a new location-coding protocol in a diverse population showed that adult PA locations varied by PA intensity, sociodemographic characteristics, BMI, and geographic location. Although homes, roads, and parks remain important locations for demographically targeted PA interventions, observed usage patterns by participant characteristics may facilitate development of more appropriately targeted interventions.

Relationship between school dropout and teen pregnancy among rural South African young women.

BACKGROUND: Sexual activity may be less likely to occur during periods of school enrolment because of the structured and supervised environment provided, the education obtained and the safer peer networks encountered while enrolled. We examined whether school enrolment was associated with teen pregnancy in South Africa. METHODS: Using longitudinal demographic surveillance data from the rural Agincourt sub-district, we reconstructed the school enrolment status from 2000 through 2011 for 15 457 young women aged 12-18 years and linked them to the estimated conception date for each pregnancy during this time. We examined the effect of time-varying school enrolment on teen pregnancy using a Cox proportional hazard model, adjusting for: age; calendar year; household socioeconomic status; household size; and gender, educational attainment and employment of household head. A secondary analysis compared the incidence of pregnancy among school enrolees by calendar time: school term vs school holiday. RESULTS: School enrolment was associated with lower teen pregnancy rates [adjusted hazard ratio (95% confidence interval): 0.57 (0.50, 0.65)].This association was robust to potential misclassification of school enrolment. For those enrolled in school, pregnancy occurred less commonly during school term than during school holidays [incidence rate ratio (95% confidence interval): 0.90 (0.78, 1.04)]. CONCLUSIONS: Young women who drop out of school may be at higher risk for teen pregnancy and could likely benefit from receipt of accessible and high quality sexual health services. Preventive interventions designed to keep young women in school or addressing the underlying causes of dropout may also help reduce the incidence of teen pregnancy.

Highly localized sensitivity to climate forcing drives endemic cholera in a megacity.

The population dynamics of endemic cholera in urban environments--in particular interannual variation in the size and distribution of seasonal outbreaks--remain poorly understood and highly unpredictable. In part, this situation is due to the considerable demographic, socioeconomic, and environmental heterogeneity of large and growing urban centers. Despite this heterogeneity, the influence of climate variability on the population dynamics of infectious diseases is considered a large-scale, regional, phenomenon, and as such has been previously addressed for cholera only with temporal models that do not incorporate spatial structure. Here we show that a probabilistic spatial model can explain cholera dynamics in the megacity of Dhaka, Bangladesh, and afford a basis for cholera forecasts at lead times of 11 mo. Critically, we find that the action of climate variability (El Niño southern oscillation and flooding) is quite localized: There is a climate-sensitive urban core that acts to propagate risk to the rest of the city. The modeling framework presented here should be applicable to cholera in other cities, as well as to other infectious diseases in urban settings and other biological systems with spatiotemporal interactions.

Molecular malaria epidemiology: mapping and burden estimates for the Democratic Republic of the Congo, 2007.

BACKGROUND: Epidemiologic data on malaria are scant in many high-burden countries including the Democratic Republic of the Congo (DRC), which suffers the second-highest global burden of malaria. Malaria control efforts in regions with challenging infrastructure require reproducible and efficient surveillance. We employed new high-throughput molecular testing to characterize the state of malaria control in the DRC and estimate childhood mortality attributable to excess malaria transmission. METHODS AND FINDINGS: The Demographic and Health Survey was a cross-sectional, population-based cluster household survey of adults aged 15-59 years in 2007 employing structured questionnaires and dried blood spot collection. Parasitemia was detected by real-time PCR, and survey responses measured adoption of malaria control measures and under-5 health indices. The response rate was 99% at the household level, and 8,886 households were surveyed in 300 clusters; from 8,838 respondents molecular results were available. The overall prevalence of parasitemia was 33.5% (95% confidence interval [C.I.] 32-34.9); P. falciparum was the most prevalent species, either as monoinfection (90.4%; 95% C.I. 88.8-92.1) or combined with P. malariae (4.9%; 95% C.I. 3.7-5.9) or P. ovale (0.6%; 95% C.I. 0.1-0.9). Only 7.7% (95% CI 6.8-8.6) of households with children under 5 owned an insecticide-treated bednet (ITN), and only 6.8% (95% CI 6.1-7.5) of under-fives slept under an ITN the preceding night. The overall under-5 mortality rate was 147 deaths per 1,000 live births (95% C.I. 141-153) and between clusters was associated with increased P. falciparum prevalence; based on the population attributable fraction, 26,488 yearly under-5 deaths were attributable to excess malaria transmission. CONCLUSIONS: Adult P. falciparum prevalence is substantial in the DRC and is associated with under-5 mortality. Molecular testing offers a new, generalizable, and efficient approach to characterizing malaria endemicity in underserved countries.

Spatial and socio-behavioral patterns of HIV prevalence in the Democratic Republic of Congo.

This study uses a 2007 population-based household survey to examine the individual and community-level factors that increase an individual's risk for HIV infection in the Democratic Republic of Congo (DRC). Using the 2007 DRC Demographic Health Surveillance (DHS) Survey, we use spatial analytical methods to explore sub-regional patterns of HIV infection in the DRC. Geographic coordinates of survey communities are used to map prevalence of HIV infection and explore geographic variables related to HIV risk. Spatial cluster techniques are used to identify hotspots of infection. HIV prevalence is related to individual demographic characteristics and sexual behaviors and community-level factors. We found that the prevalence of HIV within 25 km of an individual's community is an important positive indicator of HIV infection. Distance from a city is negatively associated with HIV infection overall and for women in particular. This study highlights the importance of improved surveillance systems in the DRC and other African countries along with the use of spatial analytical methods to enhance understanding of the determinants of HIV infection and geographic patterns of prevalence, thereby contributing to improved allocation of public health resources in the future.

Spatial proximity and the risk of psychopathology after a terrorist attack.

Previous studies concerned with the relation of proximity to the September 11, 2001 terrorist attacks and subsequent psychopathology have produced conflicting results. The goals of this analysis are to assess the appropriateness of using Bayesian hierarchical spatial techniques to answer the question of the role of proximity to a mass trauma as a risk factor for psychopathology. Using a set of individual-level Medicaid data for New York State, and controlling for age, gender, median household income and employment-related exposures, we applied Bayesian hierarchical modeling methods for spatially aggregated data. We found that distance from the World Trade Center site in the post-attack time period was associated with increased risk of anxiety-related diagnoses. In the months following the attack, each 2-mile increment in distance closer to the World Trade Center site was associated with a 7% increase in anxiety-related diagnoses in the population. No similar association was found during a similar time period in the year prior to the attack. We conclude that spatial variables help more fully describe post-terrorism psychiatric risk and may help explain discrepancies in the existing literature about these attacks. These methods hold promise for the characterization of disease risk where spatial patterning of ecologic-level exposures and outcomes merits consideration.

Evidence of localized clustering of gastroschisis births in North Carolina, 1999-2004.

Examining the geographic distribution of birth defects can be useful in exploratory etiologic research. Identification of clusters of certain defects may uncover possible environmental or socio-economic risk factors and assist with the generation of hypotheses about underlying causes of these conditions. In North Carolina, the prevalence of gastroschisis, a serious abdominal wall defect, has increased over the past decade and anecdotal evidence from clinicians suggests the possibility of clustering of this condition. This study uses a spatial scan statistic to identify the location and extent of clusters of gastroschisis births in North Carolina between 1999 and 2004. Data on cases of gastroschisis were obtained from the North Carolina Birth Defect Monitoring Program (NCBDMP) and control births were chosen from all resident live births without birth defects contained in the North Carolina composite linked birth files. The clusters were controlled for five major risk factors (maternal age, race, parity, Medicaid status, maternal smoking) to ensure that the clusters were not artifacts of unequal population distribution. Results indicate a localized cluster of gastroschisis in the rural southern Piedmont of North Carolina which persists even after controlling for all major risk factors. Adjusting for these risk factors shifted the location of the cluster substantially, demonstrating the importance of adjusting for underlying population distribution. Since clusters persisted after adjusting for individual-level risk factors, environmental contaminants may explain the excess of gastroschisis cases. This study is among the first to assess spatial clustering of gastroschisis using GIS methods. This study also demonstrates the importance of controlling for covariates in spatial analysis and illustrates the usefulness of the spatial scan statistic in exploratory etiologic research.