Public health related tweets are difficult to identify in large conversational datasets like Twitter.com. Even more challenging is the visualization and analyses of the spatial patterns encoded in tweets. This study has the following objectives: How can topic modeling be used to identify relevant public health topics such as obesity on Twitter.com? What are the common obesity related themes? What is the spatial pattern of the themes? What are the research challenges of using large conversational datasets from social networking sites? Obesity is chosen as a test theme to demonstrate the effectiveness of topic modeling using Latent Dirichlet Allocation (LDA) and spatial analysis using Geographic Information System (GIS). The dataset is constructed from tweets (originating from the United States) extracted from Twitter.com on obesity-related queries. Examples of such queries are ‘food deserts’, ‘fast food’, and ‘childhood obesity’. The tweets are also georeferenced and time stamped. Three cohesive and meaningful themes such as ‘childhood obesity and schools’, ‘obesity prevention’, and ‘obesity and food habits’ are extracted from the LDA model. The GIS analysis of the extracted themes show distinct spatial pattern between rural and urban areas, northern and southern states, and between coasts and inland states. Further, relating the themes with ancillary datasets such as US census and locations of fast food restaurants based upon the location of the tweets in a GIS environment opened new avenues for spatial analyses and mapping. Therefore the techniques used in this study provide a possible toolset for computational social scientists in general and health researchers in specific to better understand health problems from large conversational datasets.

Social network analysis (SNA) and social network-based interventions (SNI) are important analytical tools harnessing peer and family influences critical for HIV prevention and treatment among substance users. While SNA is an effective way to measure social network influences, SNI directly or indirectly involves network members in interventions. Even though these methods have been applied in heterogeneous ways, leading to extensive evidence-based practices, systematic reviews are however, lacking. We searched five bibliographic databases and identified 58 studies involving HIV in substance users that had utilized SNA or SNI as part of their methodology. SNA was used to measure network variables as inputs in statistical/mathematical models in 64% of studies and only 22% of studies used SNI. Most studies focused on HIV prevention and few addressed diagnosis (k=4), care linkage and retention (k=5), ART adherence (k=2), and viral suppression (k=1). This systematic review highlights both the advantages and disadvantages of social network approaches for HIV prevention and treatment and gaps in its use for HIV care continuum.

The grocery retail industry is encountering unique challenges and opportunities during the 2019 Novel Coronavirus (COVID-19). The pandemic led to various transformations in the food retail industry, including changes in consumer perception and behavior. Although the pandemic has a situational nature, these transformations could have both temporary and long-lasting effects on reforms of the grocery retail industry. We examined consumer retail grocery shopping behavior change during the pandemic using a national survey among 2500 U.S. adults. Survey results show that consumers now have higher expectations for in-store safety; they have reduced the frequency of store patronage, travel time, and in-store duration; they have shifted from regular shopping schedule and shopping destinations; and they have spent more per shopping trip. The increased spending at brick-and-mortar stores also paralleled with the expanded transactions across various types of online grocery shopping platforms. We further arrived at practical managerial implications in both the short term and long term for brick-and-mortar stores as well as online grocery vendors.

The disinclination of chain supermarkets to locate or pull out existing stores from impoverished neighborhoods is termed as “supermarket redlining”. This paper attempts to map and understand the spatial effects of potential supermarket redlining on food vulnerability in urban disadvantaged neighborhoods of Hartford, Connecticut. Using a combination of statistical and spatial analysis functions, we first, built a Supermarket Redlining Index (SuRI) from five indicators such as sales volume, employee count, accepts food coupons from federally assisted programs, and size and population density of the service area to rank supermarkets in the order of their importance. Second, to understand the effect of redlining, a Supermarket Redlining Impact Model (SuRIM) was built with eleven indicators describing both the socioeconomic and food access vulnerabilities. The interaction of these vulnerabilities would identify the final outcome: neighborhoods where the impact of supermarket redlining would be critical. Results mapped critical areas in the inner-city of Hartford where if a nearby supermarket closes or relocates to a suburb with limited mitigation efforts to gill the grocery gap, a large number of minority, poor, and disadvantaged residents will experience difficulties to access healthy food leading to food insecurity or perhaps a food desert. We also suggest mitigation efforts to reduce the impact of large supermarket closures.

The Government of India considers prenatal care programs as a priority activity for promoting safe motherhood and child survival. It relies heavily on electronic mass media, including radio, television, and cinema to educate mothers-two-thirds of whom are illiterate-about prenatal check-ups and timing, iron prophylaxis, and tetanus toxoid injections. This study evaluated the effect of mothers' exposure to electronic mass media on knowledge and use of prenatal care services, using data from India's 1998-1999 National Family Health Survey. Multivariate logistic regressions were used to estimate the effects of media exposure by calculating odds ratios of each of the four response variables (complete prenatal care services, prenatal check-ups, tetanus toxoid injections, and iron prophylaxes) for exposure to mass media. The results indicated that exposure to mass media is related to the use of prenatal care services even when other likely causes of the relationships are statistically controlled at their mean. The effect also showed a north-south divide among the Indian States, being stronger in northern states as compared with southern states.