Program in Public Health

Qualitative work has found that Latino food pantry recipients share food and reciprocally provide social support to their food-insecure neighbors. These findings suggest that neighborhood cohesion (NC) may serve as an important community-level resource that Latinos utilize as a coping mechanism when food-insecure. High levels of NC may be a proxy for instrumental support outside the household and act as a buffer against the adverse health effects of food insecurity including type 2 diabetes (T2D), which is highly sensitive to food insecurity. The purpose of this study was to quantitatively test this theory by examining whether NC moderated the association between T2D and food security (FS) status among Latino adults nationwide. We used data from the 2013-2018 National Health Interview Survey (n = 23,478). We found that FS status was associated with T2D prevalence, with Latino adults having a higher odds of T2D if they had low FS or very low FS compared to their FS counterparts. We also found Latinos adults who reported high NC had a lower odds of T2D compared to those who reported low NC. However, we did not find there was significant interaction between FS status and NC on T2D. NC may instead be a precursor to FS status, rather than a buffer of food insecurity on T2D. Low NC may lead to less instrumental support and tangible benefits that determine FS. Additionally, perceived NC might not align with objective NC and T2D may be too distal of a health outcome to test the protective effect of NC.

Knowledge of insect dispersal is relevant to the control of agricultural pests, vector-borne transmission of human and veterinary pathogens, and insect biodiversity. Previous studies in a malaria endemic area of the Sahel region in West Africa revealed high-altitude, long-distance migration of insects and various mosquito species. The objective of the current study was to assess whether similar behavior is exhibited by mosquitoes and other insects around the Lake Victoria basin region of Kenya in East Africa. Insects were sampled monthly from dusk to dawn over 1 year using sticky nets suspended on a tethered helium-filled balloon. A total of 17,883 insects were caught on nets tethered at 90, 120, and 160 m above ground level; 818 insects were caught in control nets. Small insects (<0.5 cm, n = 15,250) were predominant regardless of height compared with large insects (>0.5 cm, n = 2,334) and mosquitoes (n = 299). Seven orders were identified; dipteran was the most common. Barcoding molecular assays of 184 mosquitoes identified 7 genera, with Culex being the most common (65.8%) and Anopheles being the least common (5.4%). The survival rate of mosquitoes, experimentally exposed to high-altitude overnight, was significantly lower than controls maintained in the laboratory (19% vs. 85%). There were no significant differences in mosquito survival and oviposition rate according to capture height. These data suggest that windborne dispersal activity of mosquito vectors of malaria and other diseases occurs on a broad scale in sub-Saharan Africa.

Insecticide resistance in Aedes mosquitoes presents a major challenge to the control of arboviral diseases. However, resistance mechanisms for many of the insecticides remain unknown. A commonly used insecticide, deltamethrin, was used to select a resistance strain of the vector mosquito, Aedes albopictus, and we identified an F1534S substitution in the voltage-gated sodium channel (VGSC) gene product as the first event in generating resistance. Engineering an F1534S substitution using Cas9/gRNA technologies conferred deltamethrin resistance on a previously susceptible strain. Crosses that removed this mutation restored the susceptible phenotype. Predicted protein structural changes and differences in transcript accumulation levels were correlated with the resistance phenotype. Furthermore, F1534S mutations were detected in all resistant Ae. albopictus populations collected in the field. We conclude that the VGSC F1534S mutation is essential for resistance to deltamethrin in Ae. albopictus, and is a suitable molecular index for pyrethroid resistance detection and monitoring in this species.

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Combining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis transmission in high-burden tuberculosis (TB) settings. We performed whole-genome sequencing on M. tuberculosis DNA extracted from sputum cultures from a population-based TB study conducted in Gaborone, Botswana, during 2012-2016. We determined spatial distribution of cases on the basis of shared genotypes among isolates. We considered clusters of isolates with ≤5 single-nucleotide polymorphisms identified by whole-genome sequencing to indicate recent transmission and clusters of ≥10 persons to be outbreaks. We obtained both molecular and geospatial data for 946/1,449 (65%) participants with culture-confirmed TB; 62 persons belonged to 5 outbreaks of 10-19 persons each. We detected geospatial clustering in just 2 of those 5 outbreaks, suggesting heterogeneous spatial patterns. Our findings indicate that targeted interventions applied in smaller geographic areas of high-burden TB identified using integrated genomic and geospatial data might help interrupt TB transmission during outbreaks.

Despite global investments in malaria eradication and mitigation efforts, including the dissemination of ITNs to vulnerable communities, the goal of widespread malaria control among pregnant women has yet to be realized in many African countries. One of the explanations forwarded for this is related to the adoption and regular use of ITNs by pregnant women. Based on the available DHS and MIS data from four malaria high burden African countries- according to WHO malaria report 2020- inequality was measured by applying both relative and absolute summary measures for the four dimensions of inequality: economic status, education, place of residence and region. By considering the number of subgroups in each variable, simple and complex summary measures were used.ITN utilization by pregnant women showed an increasing trend over time in all the four countries. There was also significant inequality (variability) in the ITN utilization among population groups. DRC, Mozambique and Uganda showed noticeable inequality that favors the richest population, whereas in Nigeria the inequality was observed among both the rich and the poor during different survey yearsIn conclusion, in all the four countries, there were significant regional variations or differences in ITN use among pregnant mothers across all dimensions of inequality in the survey years. Tailored cost-effective interventions could be considered to improve ITN utilization among pregnant women.

Mechanistic models fit to streaming surveillance data are critical to understanding the transmission dynamics of an outbreak as it unfolds in real-time. However, transmission model parameter estimation can be imprecise, and sometimes even impossible, because surveillance data are noisy and not informative about all aspects of the mechanistic model. To partially overcome this obstacle, Bayesian models have been proposed to integrate multiple surveillance data streams. We devised a modeling framework for integrating SARS-CoV-2 diagnostics test and mortality time series data, as well as seroprevalence data from cross-sectional studies, and tested the importance of individual data streams for both inference and forecasting. Importantly, our model for incidence data accounts for changes in the total number of tests performed. We model the transmission rate, infection-to-fatality ratio, and a parameter controlling a functional relationship between the true case incidence and the fraction of positive tests as time-varying quantities and estimate changes of these parameters nonparametrically. We compare our base model against modified versions which do not use diagnostics test counts or seroprevalence data to demonstrate the utility of including these often unused data streams. We apply our Bayesian data integration method to COVID-19 surveillance data collected in Orange County, California between March 2020 and February 2021 and find that 32--72\% of the Orange County residents experienced SARS-CoV-2 infection by mid-January, 2021. Despite this high number of infections, our results suggest that the abrupt end of the winter surge in January 2021 was due to both behavioral changes and a high level of accumulated natural immunity.

Aedes mosquitoes are some of the most important and globally expansive vectors of disease. Public health efforts are largely focused on prevention of human-vector contact. A range of entomological indices are used to measure risk of disease, though with conflicting results (i.e. larval or adult abundance does not always predict risk of disease). There is a growing interest in the development and use of biomarkers for exposure to mosquito saliva, including for Aedes spp, as a proxy for disease risk. In this study, we conduct a comprehensive geostatistical analysis of exposure to Aedes mosquito bites among a pediatric cohort in a peri‑urban setting endemic to dengue, Zika, and chikungunya viruses. We use demographic, household, and environmental variables (the flooding index (NFI), land type, and proximity to a river) in a Bayesian geostatistical model to predict areas of exposure to Aedes aegypti bites. We found that hotspots of exposure to Ae. aegypti salivary gland extract (SGE) were relatively small (< 500 m and sometimes < 250 m) and stable across the two-year study period. Age was negatively associated with antibody responses to Ae. aegypti SGE. Those living in agricultural settings had lower antibody responses than those living in urban settings, whereas those living near recent surface water accumulation were more likely to have higher antibody responses. Finally, we incorporated measures of larval and adult density in our geostatistical models and found that they did not show associations with antibody responses to Ae. aegypti SGE after controlling for other covariates in the model. Our results indicate that targeted house- or neighborhood-focused interventions may be appropriate for vector control in this setting. Further, demographic and environmental factors more capably predicted exposure to Ae. aegypti mosquitoes than commonly used entomological indices.

Health care among forcibly displaced persons is frequently driven by siloed approaches. Aspects of the built environment, social factors, and the bidirectional relationship between the changing ecosystem and residents are often ignored in health policy design and implementation. While recognizing factors that create a preference for siloed approaches and appreciating the work of humanitarian agencies, we argue for a new data-driven and holistic approach to understand the health of the forcibly displaced. It should be rooted in the realities of the emergence of new diseases, dynamic demographics, and degrading environments around the displaced communities. Such an approach envisions refugee and internally displaced camps as dynamic, complex ecosystems that alter, and are altered by, spatial and temporal factors. At the root of this approach is the necessity to work across disciplines, to think holistically, to go beyond treating single ailments, and to develop ethical approaches that provide dignity to those who are forcibly displaced.

The mitochondrial marker, COII, was employed to assess the genetic structure and diversity of Anopheles funestus, a very important malaria vector in Africa that adapt and colonize different ecological niches in western Kenya. Mosquitoes were collected using mechanical aspirators in four areas (Bungoma, Port Victoria, Kombewa, and Migori) in western Kenya. Following morphological identification, PCR was used to confirm the species. The COII gene was amplified, sequenced, and analyzed to determine genetic diversity and population structure. A total of 126 (Port Victoria-38, Migori-38, Bungoma-22, and Kombewa-28) sequences of COII were used for population genetic analysis. Anopheles funestus had a high haplotype diversity (Hd = 0.97 to 0.98) but low nucleotide diversity (Π = 0.004 to 0.005). The neutrality test revealed negative Tajima's D and Fs values indicating an excess of low-frequency variation. This could be attributed to either population expansion or negative selection pressure across all the populations. No genetic or structural differentiation (Fst = -0.01) and a high level of gene flow (Gamma St, Nm = 17.99 to 35.22) were observed among the populations. Population expansion suggests the high adaptability of this species to various ecological requirements, hence sustaining its vectorial capacity and malaria transmission.