Antimicrobial Resistance Patterns of Outpatient Staphylococcus aureus Isolates.

Importance: Oral non-ß-lactam antibiotics are commonly used for empirical therapy of Staphylococcus aureus infections, especially in outpatient settings. However, little is known about potential geographic heterogeneity and temporal trends in the prevalence of S aureus resistance to non-ß-lactams in the US. Objective: To characterize the spatiotemporal trends of resistance to non-ß-lactam antibiotics among community-onset S aureus infections, including regional variation in resistance rates and geographical heterogeneity in multidrug resistance. Design, Setting, and Participants: This cross-sectional study used data from Veterans Health Administration clinics collected from adult outpatients with S aureus infection in the conterminous 48 states and Washington, DC, from January 1, 2010, to December 31, 2019. Data were analyzed from January to November 2023. Exposures: Resistance to lincosamides (clindamycin), tetracyclines, sulfonamides (trimethoprim-sulfamethoxazole [TMP-SMX]), and macrolides. Main Outcomes and Measures: Spatiotemporal variation of S aureus resistance to these 4 classes of non-ß-lactam antibiotics, stratified by methicillin-resistant S aureus (MRSA) and methicillin-sensitive S aureus (MSSA), and subdivided by regions of the US (Northeast, Midwest, South, and West). Trend tests and bivariate mapping were used to determine significant changes in resistant proportions over time and identify counties where rates of resistance to multiple non-ß-lactams were high. Results: A total of 382 149 S aureus isolates from 268 214 unique outpatients (mean [SD] age, 63.4 [14.8] years; 252 910 males [94.29%]) were analyzed. There was a decrease in the proportion of MRSA nationwide, from 53.6% in 2010 to 38.8% in 2019. Among MRSA isolates, we observed a significant increase in tetracycline resistance (from 3.6% in 2010 to 12.8% in 2019; P for trend < .001) and TMP-SMX resistance (from 2.6% in 2010 to 9.2% in 2019; P for trend < .001), modest and not significant increases in clindamycin resistance (from 24.2% in 2010 to 30.6% in 2019; P for trend = .34), and a significant decrease in macrolide resistance (from 73.5% in 2010 to 60.2% in 2019; P for trend < .001). Among MSSA isolates, significant upward trends in clindamycin, tetracyclines, and TMP-SMX resistance were observed. For example, tetracycline resistance increased from 3.7% in 2010 to 9.1% in 2019 (P for trend < .001). Regional stratification over time showed that the Northeast had slightly higher rates of clindamycin resistance but lower rates of tetracycline resistance, while the South had notably higher rates of resistance to tetracyclines and TMP-SMX, particularly among MRSA isolates. Bivariate mapping at the county scale did not indicate clear regional patterns of shared high levels of resistance to the 4 classes of antimicrobials studied. Conclusions and Relevance: In this study of outpatient S aureus isolates, MRSA became less common over the 10-year period, and MRSA isolates were increasingly resistant to tetracyclines and TMP-SMX. Geographic analysis indicated no spatial overlap in counties with high rates of resistance to both tetracyclines and TMP-SMX. Examining the regional spatial variation of antibiotic resistance can inform empirical therapy recommendations and help to understand the evolution of S aureus antibiotic resistance mechanisms.

Assessing the potential for improved predictive capacity of antimicrobial resistance in outpatient Staphylococcus aureus isolates using seasonal and spatial antibiograms.

BACKGROUND: While the use of cumulative susceptibility reports, antibiograms, is recommended for improved empiric therapy and antibiotic stewardship, the predictive ability of antibiograms has not been well-studied. While enhanced antibiograms have been shown to better capture variation in susceptibility profiles by characteristics such as infection site or patient age, the potential for seasonal or spatial variation in susceptibility has not been assessed as important in predicting likelihood of susceptibility. METHODS: Utilizing Staphylococcus aureus isolates obtained in outpatient settings from a nationwide provider of care, the Veterans Health Administration, and a local provider of care, the University of Iowa Hospitals and Clinics, standard, seasonal and spatial antibiograms were created for five commonly used antibiotic classes: cephalosporins, clindamycin, macrolides, tetracycline, trimethoprim/sulfamethoxazole. RESULTS: A total of 338,681 S. aureus isolates obtained in VHA outpatient settings from 2010 to 2019 and 6,817 isolates obtained in UIHC outpatient settings from 2014 to 2019 were used to generate and test antibiograms. Logistic regression modeling determined the capacity of these antibiograms to predict isolate resistance to each antibiotic class. All models had low predictive capacity, with areas under the curve of < 0.7. CONCLUSIONS: Standard antibiograms are poor in predicting S. aureus susceptibility to antibiotics often chosen by clinicians, and seasonal and spatial antibiograms do not provide an improved tool in anticipating non-susceptibility. These findings suggest that further refinements to antibiograms may be necessary to improve their utility in informing choice of effective antibiotic therapy.

Spatiotemporal distribution of community-acquired phenotypic extended-spectrum beta-lactamase Escherichia coli in United States counties, 2010-2019.

Using data from the Veterans' Health Administration from 2010 to 2019, we examined the distribution and prevalence of community-acquired phenotypic extended-spectrum ß-lactamase (ESBL) E. coli in the United States. ESBL prevalence slowly increased during the study period, and cluster analysis showed clustering in both urban and rural locations.

Persistence of potential ST398 MSSA in outpatient settings among US veterans, 2010-2019.

Novel ST398 methicillin susceptible Staphylococcus aureus (MSSA) in the United States was first observed in New York City (2004-2007); its diffusion across the country resulted in changing treatment options. Utilizing outpatient antimicrobial susceptibility data from the Veterans Health Administration from 2010 to 2019, the spatiotemporal prevalence of potential ST398 MSSA is documented.

Epidemiology of Plasmodium malariae and Plasmodium ovale spp. in a highly malaria-endemic country: a longitudinal cohort study in Kinshasa Province, Democratic Republic of Congo.

Background: Increasing reports suggest that non-falciparum species are an underappreciated cause of malaria in sub-Saharan Africa, but their epidemiology is not well-defined. This is particularly true in regions of high P. falciparum endemicity such as the Democratic Republic of Congo (DRC), where 12% of the world's malaria cases and 13% of deaths occur. Methods and Findings: The cumulative incidence and prevalence of P. malariae and P. ovale spp. infection detected by real-time PCR were estimated among children and adults within a longitudinal study conducted in seven rural, peri-urban, and urban sites from 2015-2017 in Kinshasa Province, DRC. Participants were sampled at biannual household survey visits (asymptomatic) and during routine health facility visits (symptomatic). Participant-level characteristics associated with non-falciparum infections were estimated for single- and mixed-species infections. Among 9,089 samples collected from 1,565 participants over a 3-year period, the incidence of P. malariae and P. ovale spp. infection was 11% (95% CI: 9%-12%) and 7% (95% CI: 5%-8%) by one year, respectively, compared to a 67% (95% CI: 64%-70%) one-year cumulative incidence of P. falciparum infection. Incidence continued to rise in the second year of follow-up, reaching 26% and 15% in school-age children (5-14yo) for P. malariae and P. ovale spp., respectively. Prevalence of P. malariae, P. ovale spp., and P. falciparum infections during household visits were 3% (95% CI: 3%-4%), 1% (95% CI: 1%-2%), and 35% (95% CI: 33%-36%), respectively. Non-falciparum malaria was more prevalent in rural and peri-urban vs. urban sites, in school-age children, and among those with P. falciparum co-infection. A crude association was detected between P. malariae and any anemia in the symptomatic clinic population, although this association did not hold when stratified by anemia severity. No crude associations were detected between non-falciparum infection and fever prevalence. Conclusions: P. falciparum remains the primary driver of malaria morbidity and mortality in the DRC. However, non-falciparum species also pose an infection risk across sites of varying urbanicity and malaria endemicity within Kinshasa, DRC, particularly among children under 15 years of age. As P. falciparum interventions gain traction in high-burden settings like the DRC, continued surveillance and improved understanding of non-falciparum infections are warranted.

Epidemiology of Plasmodium malariae and Plasmodium ovale spp. in Kinshasa Province, Democratic Republic of Congo.

Reports suggest non-falciparum species are an underappreciated cause of malaria in sub-Saharan Africa but their epidemiology is ill-defined, particularly in highly malaria-endemic regions. We estimated incidence and prevalence of PCR-confirmed non-falciparum and Plasmodium falciparum malaria infections within a longitudinal study conducted in Kinshasa, Democratic Republic of Congo (DRC) between 2015-2017. Children and adults were sampled at biannual household surveys and routine clinic visits. Among 9,089 samples from 1,565 participants, incidences of P. malariae, P. ovale spp., and P. falciparum infections by 1-year were 7.8% (95% CI: 6.4%-9.1%), 4.8% (95% CI: 3.7%-5.9%) and 57.5% (95% CI: 54.4%-60.5%), respectively. Non-falciparum prevalences were higher in school-age children, rural and peri-urban sites, and P. falciparum co-infections. P. falciparum remains the primary driver of malaria in the DRC, though non-falciparum species also pose an infection risk. As P. falciparum interventions gain traction in high-burden settings, continued surveillance and improved understanding of non-falciparum infections are warranted.

Spatial and temporal trends of overweight/obesity and tobacco use in East Africa: subnational insights into cardiovascular disease risk factors.

BACKGROUND: Cardiovascular disease (CVD) is increasing in Sub-Saharan Africa (SSA). Overweight/obesity and tobacco use are modifiable CVD risk factors, however literature about the spatiotemporal dynamics of these risk factors in the region at subnational or local scales is lacking. We describe the spatiotemporal trends of overweight/obesity and tobacco use at subnational levels over a 13-year period (2003 to 2016) in five East African nations. METHODS: Cross-sectional, nationally representative Demographic and Health Surveys (DHS) were used to explore the subnational spatiotemporal patterns of overweight/obesity and tobacco use in Burundi, Kenya, Rwanda, Tanzania, and Uganda, five East African Community (EAC) nations with unique cultural landscapes influencing CVD risk factors. Adaptive kernel density estimation and logistic regression were used to determine the spatial distribution and change over time of CVD risk factors on a subnational and subpopulation (rural/urban) scale. RESULTS: Subnational analysis shows that regional and national level analysis masks important trends in CVD risk factor prevalence. Overweight/obesity and tobacco use trends were not similar: overweight/obesity prevalence increased across most nations included in the study and the inverse was true for tobacco use prevalence. Urban populations in each nation were more likely to be overweight/obese than rural populations, but the magnitude of difference varied widely between nations. Spatial analysis revealed that although the prevalence of overweight/obesity increased over time in both urban and rural populations, the rate of change differed between urban and rural areas. Rural populations were more likely to use tobacco than urban populations, though the likelihood of use varied substantially between nations. Additionally, spatial analysis showed that tobacco use was not evenly distributed across the landscape: tobacco use increased in and around major cities and urban centers but declined in rural areas. CONCLUSIONS: We highlight the importance of de-homogenizing CVD risk factor research in SSA. Studies of national or regional prevalence trends mask important information about subpopulation and place-specific behavior and drivers of risk factor prevalence. Spatially explicit studies should be considered as a vital tool to understand local drivers of health, disease, and associated risk factor trends, especially in highly diverse yet low-resourced, marginalized, and often homogenized regions.

How human ecology landscapes shape the circulation of H5N1 avian influenza: A case study in Indonesia.

Background: Highly pathogenic avian influenza H5N1 virus consistently threatens global public health. A better understanding of the virus' circulation mechanism is needed for future epidemic prevention. Previous studies have focused on the correlations between the presence of H5N1 virus and wild bird populations, domestic poultry production, and sociodemographic factors. However, human cultural landscapes and their impact on H5N1 spread have not been adequately explored. Methods: Using 196 HA gene sequences of H5N1 influenza viruses from Indonesia with district-level geographic information, we performed Monmonier barrier and Louvain community detection analyses to explore how human ecological factors impact the circulation of virus and identify barriers to or corridors of dispersal. Results: Spatial discontinuity in the genetic characteristics identified by the Monmonier algorithm were found to mirror the differences in key landscape factors. Our Louvain community detection analysis also found the co-existence of different geographic circulation patterns. The community detection analysis suggests that direct human-related interactions such as poultry transportations between remote areas may result in similar viruses spreading in two distant regions whilst dense localities supported genetically heterogeneous viruses in geographically adjacent areas. Conclusion: Human ecological landscapes shape the circulation mechanism of H5N1 virus in multiple ways contingent upon local context. Physical and cultural barriers may impede its movement between adjacent areas, while natural or human-induced corridors such as wild bird flyways and poultry production networks facilitate its spread between geographically distant areas. Further focus on the importance of cultural landscapes has great potential for increasing our understanding of the circulation of pathogenic H5N1 avian influenza virus in Southeast Asia.

Spatial genetic structure of 2009 H1N1 pandemic influenza established as a result of interaction with human populations in mainland China.

Identifying the spatial patterns of genetic structure of influenza A viruses is a key factor for understanding their spread and evolutionary dynamics. In this study, we used phylogenetic and Bayesian clustering analyses of genetic sequences of the A/H1N1pdm09 virus with district-level locations in mainland China to investigate the spatial genetic structure of the A/H1N1pdm09 virus across human population landscapes. Positive correlation between geographic and genetic distances indicates high degrees of genetic similarity among viruses within small geographic regions but broad-scale genetic differentiation, implying that local viral circulation was a more important driver in the formation of the spatial genetic structure of the A/H1N1pdm09 virus than even, countrywide viral mixing and gene flow. Geographic heterogeneity in the distribution of genetic subpopulations of A/H1N1pdm09 virus in mainland China indicates both local to local transmission as well as broad-range viral migration. This combination of both local and global structure suggests that both small-scale and large-scale population circulation in China is responsible for viral genetic structure. Our study provides implications for understanding the evolution and spread of A/H1N1pdm09 virus across the population landscape of mainland China, which can inform disease control strategies for future pandemics.

Impacts of Hurricane Matthew Exposure on Infections and Antimicrobial Prescribing in North Carolina Veterans.

The impact of hurricane-related flooding on infectious diseases in the US is not well understood. Using geocoded electronic health records for 62,762 veterans living in North Carolina counties impacted by Hurricane Matthew coupled with flood maps, we explore the impact of hurricane and flood exposure on infectious outcomes in outpatient settings and emergency departments as well as antimicrobial prescribing. Declines in outpatient visits and antimicrobial prescribing are observed in weeks 0-2 following the hurricane as compared with the baseline period and the year prior, while increases in antimicrobial prescribing are observed 3+ weeks following the hurricane. Taken together, hurricane and flood exposure appear to have had minor impacts on infectious outcomes in North Carolina veterans, not resulting in large increases in infections or antimicrobial prescribing.

Bypassing of nearest labor & delivery unit is contingent on rurality, wealth, and race.

Patient decisions to bypass the closest labor & delivery (L&D) facility in favor of other birthing locations can have consequences for the provision of health care in rural and micropolitan areas as patient volumes decline and payer mixes change. Among 220 589 uncomplicated births in Iowa, we document characteristics of birth parents who bypass their closest birthing facility, show how this bypassing behavior results in changed travel times to delivery facilities across the rural/urban divide, and indicate the parts of the state where bypassing behavior is most prevalent. From 2013 to 2019, 55.2% of deliveries occurred in facilities that were further from birthing parents' residences than the closest L&D facility. Bypassing is associated with White, non-Hispanic race/ethnicity, and private insurance status. Although bypassing is least common among micropolitan birth parents, this group has the greatest travel burden to birthing facilities and exhibits increasing rates of bypassing over time. Perinatal quality improvement programs can target locations and populations where low-risk birthing parents can be encouraged to deliver close to home if medically appropriate, particularly in small towns and rural areas. This can potentially alleviate the risk of obstetric deserts by ensuring L&D units maintain patient volumes necessary to continue operations.

Association of Patient Proximity to Dermatologic Care With Melanoma Stage at Diagnosis and Outcome.

This cohort study evaluates the association of proximity to dermatologic clinicians with stage at diagnosis and cancer-specific survival among adults with cutaneous melanoma in Iowa.

Labor & delivery unit closures most impact travel times to birth locations for micropolitan residents in Iowa.

PURPOSE: Continued closure of rural hospitals and labor & delivery units can impact timely access to care. Iowa has lost over a quarter of its labor & delivery units in the previous decade. Calculating how travel times to labor & delivery services have changed, and where in the state the largest travel times take place, are important for understanding access to this critical service. METHODS: Using parental address and facility location from birth certificate data in Iowa from 2013 to 2019, travel times to birth facility are assessed for rural, micropolitan, and metropolitan parents, as well as for complicated versus noncomplicated births and Medicaid versus non-Medicaid recipients. FINDINGS: Parts of the state have travel times that are consistently greater than 30 minutes over the duration of the study. The largest increases in travel times are found among micropolitan residents, particularly those experiencing complicated births. Travel times are consistently the longest for rural residents but increased only slightly over the study time period. CONCLUSIONS: These findings suggest that access to hospital-based obstetric care is most changed for residents of small towns rather than rural or larger city residents.

County-level spatiotemporal distribution of fluoroquinolone-resistant Enterobacteriaceae in outpatient settings of the Veterans' Health Administration, 2000-2017.

Fluoroquinolone resistance among Enterobacteriaceae is a notable challenge for appropriate empiric therapy in outpatient settings. We describe the spatial distribution of fluoroquinolone resistance and its chronological change between 2000 and 2017 in the nationwide Veterans' Health Administration system. We found spatially concentrated increasing prevalence in the 2000s, followed by spatial dispersion in the 2010s.

Obesity treatment initiation, retention, and outcomes in the Veterans Affairs MOVE! Program among rural and urban veterans.

Objective: Rural veterans have high obesity rates. Yet, little is known about this population's engagement with the Veterans Affairs (VA) weight management program (MOVE!). The study objective is to determine whether MOVE! enrollment, anti-obesity medication use, bariatric surgery use, retention, and outcomes differ by rurality for veterans with severe obesity. Methods: This is a retrospective cohort study using Veterans Health Administration patient databases, including VA patients with severe obesity during 2015-2017. Patients were categorized using Rural-Urban Commuting Area codes. Primary outcomes included proportion of patients and risk-adjusted likelihood of initiating VA MOVE!, anti-obesity medication, or bariatric surgery and risk-adjusted highly rural|Hazard Ratio (HR) of any obesity treatment. Secondary outcomes included treatment retention (≥12 weeks) and successful weight loss (5%) among patients initiating MOVE!, and risk-adjusted odds of retention and successful weight loss. Results: Among 640,555 eligible veterans, risk-adjusted relative likelihood of MOVE! treatment was significantly lower for rural and HR veterans (HR = 0.83, HR = 0.67, respectively). Initiation rates of anti-obesity medication use were significantly lower as well, whereas bariatric surgery rates, retention, and successful weight loss did not differ. Conclusions: Overall treatment rates with MOVE!, bariatric surgery, and anti-obesity medications remain low. Rural veterans are less likely to enroll in MOVE! and less likely to receive anti-obesity medications than urban veterans.

Days of Flooding Associated with Increased Risk of Influenza.

Influenza typically causes mild infection but can lead to severe outcomes for those with compromised lung health. Flooding, a seasonal problem in Iowa, can expose many Iowans to molds and allergens shown to alter lung inflammation, leading to asthma attacks and decreased viral clearance. Based on this, the hypothesis for this research was that there would be geographically specific positive associations in locations with flooding with influenza diagnosis. An ecological study was performed using influenza diagnoses and positive influenza polymerase chain reaction tests from a de-identified large private insurance database and Iowa State Hygienic Lab. After adjustment for multiple confounding factors, Poisson regression analysis resulted in a consistent 1% associated increase in influenza diagnoses per day above flood stage (95% confidence interval: 1.00-1.04). This relationship remained after removal of the 2009-2010 influenza pandemic year. There was no associated risk between flooding and influenza-like illness as a nonspecific diagnosis. Associated risks between flooding and increased influenza diagnoses were geographically specific, with the greatest risk in the most densely populated areas. This study indicates that populations who live, work, or volunteer in flooded environments should consider preventative measures to avoid environmental exposures to mitigate illness from influenza in the following year.

Inclusion of environmentally themed search terms improves Elastic net regression nowcasts of regional Lyme disease rates.

Lyme disease is the most widely reported vector-borne disease in the United States. 95% of confirmed human cases are reported in the Northeast and upper Midwest (25,778 total confirmed cases from Northeast and upper Midwest / 27,203 total US confirmed cases). Human cases typically occur in the spring and summer months when an infected nymph Ixodid tick takes a blood meal. Current federal surveillance strategies report data on an annual basis, leading to nearly a year lag in national data reporting. These lags in reporting make it difficult for public health agencies to assess and plan for the current burden of Lyme disease. Implementation of a nowcasting model, using historical data to predict current trends, provides a means for public health agencies to evaluate current Lyme disease burden and make timely priority-based budgeting decisions. The objective of the study was to develop and compare the performance of nowcasting models using free data from Google Trends and Centers of Disease Control and Prevention surveillance reports. We developed two sets of elastic net models for five regions of the United States: 1. Using only monthly proportional hit data from the 21 disease symptoms and tick related terms, and 2. Using monthly proportional hit data from terms identified via Google correlate and the disease symptom and vector terms. Elastic net models using the full-term list were highly accurate (Root Mean Square Error: 0.74, Mean Absolute Error: 0.52, R2: 0.97) for four of the five regions of the United States and improved accuracy 1.33-fold while reducing error 0.5-fold compared to predictions from models using disease symptom and vector terms alone. Many of the terms included and found to be important for model performance were environmentally related. These models can be implemented to help local and state public health agencies accurately monitor Lyme disease burden during times of reporting lag from federal public health reporting agencies.

Delays and declines in seasonal influenza vaccinations due to Hurricane Harvey narrow annual gaps in vaccination by race, income and rurality.

OBJECTIVE: Temporal overlap of the Atlantic hurricane season and seasonal influenza vaccine rollout has the potential to result in delays or disruptions of vaccination campaigns. We documented seasonal influenza vaccination behavior over a 5-year period and explored associations between flooding following Hurricane Harvey and timing and uptake of vaccines, as well as how the impacts of Hurricane Harvey on vaccination vary by race, wealth, and rurality. DESIGN: Retrospective cohort analysis. SETTING: Texas counties affected by Hurricane Harvey. PATIENTS: Active users of the Veterans' Health Administration in 2017. METHODS: We used geocoded residential address data to assess flood exposure status following Hurricane Harvey. Days to receipt of seasonal influenza vaccines were calculated for each year from 2014 to 2019. Proportional hazards models were used to determine how likelihood of vaccination varied according to flood status as well as the race, wealth, and rural-urban residence of patients. RESULTS: The year of Hurricane Harvey was associated with a median delay of 2 weeks to vaccination and lower overall vaccination than in prior years. Residential status in flooded areas was associated with lower hazards of influenza vaccination in all years. White patients had higher proportional hazards of influenza vaccination than non-White patients, though this attenuated to 6.39% (hazard ratio [HR], 1.0639; 95% confidence interval [CI], 1.034-1.095) in the hurricane. year. CONCLUSIONS: Receipt of seasonal influenza vaccination following regional exposure to the effects of Hurricane Harvey was delayed among US veterans. White, non-low-income, and rural patients had higher likelihood of vaccination in all years of the study, but these gaps narrowed during the hurricane year.

Health Care Utilization Among Texas Veterans Health Administration Enrollees Before and After Hurricane Harvey, 2016-2018.

Importance: Hurricanes and flooding can interrupt health care utilization. Understanding the magnitude and duration of interruptions, as well as how they vary according to hazard exposure, race, and income, are important for identifying populations in need of greater retention in care. Objective: To determine how the differential exposure to Hurricane Harvey in August 2017 is associated with changes in utilization of Veterans Health Administration health care. Design, Setting, and Participants: This is a retrospective cohort analysis of primary care practitioner (PCP) visits, emergency department visits, and inpatient admissions in the Veterans Health Administration among Texas veterans residing in counties impacted by Hurricane Harvey from 2016 to 2018. Data analysis was performed from September 2020 to May 2021. Exposures: Residential flooding after Hurricane Harvey. Main Outcomes and Measures: Interrupted time series analysis measured changes in health care utilization over time, stratified by residential flood exposure, race, and income. Results: Of the 99 858 patients in the cohort, 89 931 (90.06%) were male, and their median (range) age was 58 (21 to 102) years. Compared with veterans in nonflooded areas, veterans living in flooded areas were more likely to be Black (24 715 veterans [33.80%] vs 4237 veterans [15.85%]) and low-income (14 895 veterans [20.37%] vs 4853 veterans [18.15%]). Rates of PCP visits decreased by 49.78% (95% CI, -64.52% to -35.15%) for veterans in flooded areas and by 45.89% (95% CI, -61.93% to -29.91%) for veterans in nonflooded areas and did not rebound until more than 8 weeks after the hurricane. Rates of PCP visits in flooded areas remained lower than expected for 11 weeks among White veterans (-6.99%; 95% CI, -14.36% to 0.81%) and for 13 weeks among racial minority veterans (-7.22%; 95% CI, -14.11% to 0.30%). Low-income veterans, regardless of flood status, experienced greater suppression of PCP visits in the 8 weeks following the hurricane (-13.72%; 95% CI, -20.51% to -6.68%) compared with their wealthier counterparts (-9.63%; 95% CI, -16.74% to -2.26%). Conclusions and Relevance: These findings suggest that flood disasters such as Hurricane Harvey may be associated with declines in health care utilization that differ according to flood status, race, and income strata. Patients most exposed to the disaster also had the greatest delay or nonreceipt of care.

Individual, household and neighborhood risk factors for malaria in the Democratic Republic of the Congo support new approaches to programmatic intervention.

BACKGROUND: The Democratic Republic of the Congo (DRC) remains one of the countries most impacted by malaria despite decades of control efforts, including multiple mass insecticide treated net (ITN) distribution campaigns. The multi-scalar and complex nature of malaria necessitates an understanding of malaria risk factors over time and at multiple levels (e.g., individual, household, community). Surveillance of households in both rural and urban settings over time, coupled with detailed behavioral and geographic data, enables the detection of seasonal trends in malaria prevalence and malaria-associated behaviors as well as the assessment of how the local environments within and surrounding an individual's household impact malaria outcomes. METHODS: Participants from seven sites in Kinshasa Province, DRC were followed for over two years. Demographic, behavioral, and spatial information was gathered from enrolled households. Malaria was assessed using both rapid diagnostic tests (RDT) and polymerase chain reaction (PCR) and seasonal trends were assessed. Hierarchical regression modeling tested associations between behavioral and environmental factors and positive RDT and PCR outcomes at individual, household and neighborhood scales. RESULTS: Among 1591 enrolled participants, malaria prevalence did not consistently vary seasonally across the sites but did vary by age and ITN usage. Malaria was highest and ITN usage lowest in children ages 6-15 years across study visits and seasons. Having another member of the household test positive for malaria significantly increased the risk of an individual having malaria [RDT: OR = 4.158 (2.86-6.05); PCR: OR = 3.37 (2.41-4.71)], as did higher malaria prevalence in the 250 m neighborhood around the household [RDT: OR = 2.711 (1.42-5.17); PCR: OR = 4.056 (2.3-7.16)]. Presence of water within close proximity to the household was also associated with malaria outcomes. CONCLUSIONS: Taken together, these findings suggest that targeting non-traditional age groups, children >5 years old and teenagers, and deploying household- and neighborhood-focused interventions may be effective strategies for improving malaria outcomes in high-burden countries like the DRC.