Central to developing effective control measures for the COVID-19 pandemic is understanding the epidemiology of transmission in the community. Geospatial analysis of neighborhood-level data could provide insight into drivers of infection. In the current analysis of Harris County, Texas, we used custom interpolation tools in GIS to disaggregate COVID-19 incidence estimates from the zip code to census tract estimates—a better representation of neighborhood-level estimates. We assessed the associations between 29 neighborhood-level characteristics and COVID-19 incidence using a series of aspatial and spatial models. The variables that maintained significant and positive associations with COVID-19 incidence in our final aspatial model and later represented in a geographically weighted regression model were the percentage of the Black/African American population, percentage of the foreign-born population, area derivation index (ADI), percentage of households with no vehicle, and percentage of people over 65 years old inside each census tract. Conversely, we observed negative and significant association with the percentage employed in education. Notably, the spatial models indicated that the impact of ADI was homogeneous across the study area, but other risk factors varied by neighborhood. The current findings could enhance decision making by local public health officials in responding to the COVID-19 pandemic. By understanding factors that drive community transmission, we can better target disease control measures.

Chagas disease, caused by the vector-borne parasite Trypanosoma cruzi, remains one of the most significant neglected tropical diseases affecting the Americas. Identifying high-risk populations is important for understanding Chagas disease transmission and directing public health resources. We recently hypothesized that Texas hunters may be at an elevated risk for contracting Chagas disease because of opportunities for vector exposure and contact with blood of infected reservoirs. To assess their unique exposure risks, we conducted a statewide screening program of Texas hunters. A total of 885 study participants were interviewed and tested for T. cruzi infection; 18 screened positive on a rapid, point-of-care test; however, none were found positive through confirmatory testing. We did find a high prevalence of reported direct contact with wildlife blood as well as triatomine and other arthropod disease vectors. This large-scale screening program represents a novel approach to better understand the vector-borne disease risk in this unique population.

: Diarrhea in an immunocompromised patient has a broad infectious differential. Diagnosis is difficult despite advances in diagnostic modalities. We report a case of a 45-year-old Nigerian woman who immigrated to the United States 2 years ago. She presented to the hospital with gastrointestinal bleeding, newly diagnosed HIV, and disseminated Kaposi sarcoma. During hospitalization, the patient had an onset of watery diarrhea and high eosinophilia. Subsequent stool analysis using multi-parallel real-time quantitative polymerase chain reaction for 13 parasites was positive for Cystoisospora belli. The patient was treated with trimethoprim–sulfamethoxazole, but had relapsed disease when her antibiotics were stopped prematurely. After restarting trimethoprim–sulfamethoxazole, her diarrhea and eosinophilia improved, and she had undetectable Cystoisospora belli DNA on repeat stool quantitative polymerase chain reaction. This case highlights the importance of a thorough workup for diarrhea, including parasites, especially for immunocompromised patients. Antibiotic prophylaxis is recommended in patients with Cystoisospora belli and HIV/AIDS.

In the aftermath of Hurricane Harvey in 2017, thousands of residents in the Houston area sought refuge at a convention center “megashelter”. Out of concern for the possibility of communicable diseases spreading rapidly in the crowded shelter, we conducted syndromic surveillance to monitor the health of evacuees using a digital drop-in cot-survey. The cot-to-cot survey design rapidly assessed evacuees to determine if they were experiencing any symptoms of illness each night from 1–7 September 2017. While no outbreak of a specific infection was identified during the surveillance period, runny nose, congestion, cough, achy muscles and joints, anxiety, and depression were the most commonly reported symptoms. Out of the total shelter population, 38% of adults reported symptoms compared to 25% of children (≤18 years). The cot survey took a median of 5.2 min per interview, and the daily participation rate increased throughout the surveillance period starting at 89% and ending at 96% on the last day. The success of this public health response was due, in part, to the effectiveness of survey design and the dissemination of real-time data to the health departments. Digital cot surveys can improve emergency response sustainability, interoperability among emergency responders, and improve evacuee participation.