Tanya Libby

Background: Mass azithromycin distribution reduces child mortality in some settings, potentially through reductions in nasopharyngeal carriage of Streptococcus pneumoniae, but has been associated with increased antimicrobial resistance. Individual-level data are lacking on the impact of azithromycin on antimicrobial resistance over time. Methods: We analyzed data from a double-blind, randomized placebo-controlled trial (ClinicalTrials.gov; NCT02414399) which followed 1398 hospitalized Kenyan children to evaluate the impact of a 5-day course of oral azithromycin at discharge from hospital on pneumococcal carriage and the proportion of isolates (among a random sample) resistant to azithromycin. Randomization to azithromycin or placebo (1:1) was stratified by enrollment county (Kisii or Homa Bay). Using generalized estimating equations, we calculated prevalence ratios (PRs) and 95% CIs for the intervention, adjusting for enrollment site. Results: Overall, 1253/1398 (89.6%) enrolled children received antibiotics during their hospitalization. Pneumococcal carriage at discharge was similar among children randomized to the azithromycin group (158/702 [22.5%]) compared with the placebo group (171/696 [24.6%]; P = .4) and did not differ at month 3 (65.6% versus 67.0%; PR: 0.98 [0.90, 1.06]) or month 6 (66.7% versus 66.5%; PR: 1.00 [0.92, 1.08]). At discharge, 15.7% of isolates were resistant to azithromycin and there was no difference between azithromycin-treated and placebo groups at month 3 (35/266 [13.2%] versus 32/256 [12.5%]; PR: 1.06 [0.86, 1.66]) or month 6 (41/245 [16.7%] versus 43/243 [17.6%]; PR: 1.01 [0.69, 1.49]). Conclusions: Azithromycin treatment did not effect pneumococcal carriage or antimicrobial resistance 3- or 6-months post-randomization. High inpatient antibiotic use in this recently discharged population may have reduced any further impact of azithromycin.

Background: Growing evidence links air pollution exposure to the risk of dementia. We hypothesized that hypertension may partially mediate this effect. Methods: We previously documented an association between air pollution and dementia in the Ginkgo Evaluation of Memory Study, a randomized, placebo-controlled trial of 3069 adults ≥75 years across four US sites who were evaluated for dementia every 6 months from 2000–2008. We utilized a two-stage regression approach for causal mediation analysis to decompose the total effect of air pollution on dementia into its natural direct and indirect effect through prevalent hypertension. Exposure to air pollution in the 10 or 20 years before enrollment was assigned using estimates from fine-scale spatial-temporal models for PM_2.5, PM₁₀, and NO₂. We used Poisson regression models for hypertension and Cox proportional hazard models for time-to-incident all-cause dementia, adjusting for a priori confounders. Results: Participants were free of mild cognitive impairment at baseline (n = 2564 included in analyses); 69% had prevalent hypertension at baseline. During follow-up, 12% developed all-cause dementia (Alzheimer’s disease [AD] = 212; vascular dementia with or without AD [VaD/AD mixed] = 97). We did not find an adverse effect of any air pollutant on hypertension. Hypertension was associated with VaD/AD mixed (HR, 1.92 [95% CI = 1.14, 3.24]) but not AD. We did not observe mediation through hypertension for the effect of any pollutant on dementia outcomes. Conclusions: The lack of mediated effect may be due to other mechanistic pathways and the minimal effect of air pollution on hypertension in this cohort of older adults.

Background: Despite the wealth of evidence regarding effective health behavior change techniques using digital interventions to focus on residents of high-income countries, there is limited information of a similar nature for low- and middle-income countries. Objective: The aim of this review is to identify and describe the available literature on effective social media–based behavior change interventions within low- and middle-income countries. Methods: This systematic review was conducted in accordance with the 2009 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched PubMed, Embase, Elsevier, CINAHL, PsycInfo, and Global Index Medicus, and the final search was conducted on April 6, 2021. We excluded studies published before 2000 because of the subject matter. We included studies that evaluated interventions conducted at least partly on a social media platform. Results: We identified 1832 studies, of which 108 (5.89%) passed title-abstract review and were evaluated by full-text review. In all, 30.6% (33/108) were included in the final analysis. Although 22 studies concluded that the social media intervention was effective, only 13 quantified the level of social media engagement, of which, few used theory (n=8) or a conceptual model (n=5) of behavior change. Conclusions: We identified gaps in the settings of interventions, types and sectors of interventions, length of follow-up, evaluation techniques, use of theoretical and conceptual models, and discussions of the privacy implications of social media use. Trial Registration: PROSPERO CRD42020223572; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=223572

BACKGROUND Despite the wealth of evidence regarding effective health behavior change techniques using digital interventions to focus on residents of high-income countries, there is limited information of a similar nature for low- and middle-income countries. OBJECTIVE The aim of this review is to identify and describe the available literature on effective social media–based behavior change interventions within low- and middle-income countries. METHODS This systematic review was conducted in accordance with the 2009 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched PubMed, Embase, Elsevier, CINAHL, PsycInfo, and Global Index Medicus, and the final search was conducted on April 6, 2021. We excluded studies published before 2000 because of the subject matter. We included studies that evaluated interventions conducted at least partly on a social media platform. RESULTS We identified 1832 studies, of which 108 (5.89%) passed title-abstract review and were evaluated by full-text review. In all, 30.6% (33/108) were included in the final analysis. Although 22 studies concluded that the social media intervention was effective, only 13 quantified the level of social media engagement, of which, few used theory (n=8) or a conceptual model (n=5) of behavior change. CONCLUSIONS We identified gaps in the settings of interventions, types and sectors of interventions, length of follow-up, evaluation techniques, use of theoretical and conceptual models, and discussions of the privacy implications of social media use. CLINICALTRIAL PROSPERO CRD42020223572; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=223572

It is estimated that vaccinating 50%–70% of school-aged children for influenza can produce population-wide indirect effects. We evaluated a city-wide school-located influenza vaccination (SLIV) intervention that aimed to increase influenza vaccination coverage. The intervention was implemented in ≥95 preschools and elementary schools in northern California from 2014 to 2018. Using a matched cohort design, we estimated intervention impacts on student influenza vaccination coverage, school absenteeism, and community-wide indirect effects on laboratory-confirmed influenza hospitalizations. We used a multivariate matching algorithm to identify a nearby comparison school district with pre-intervention characteristics similar to those of the intervention school district and matched schools in each district. To measure student influenza vaccination, we conducted cross-sectional surveys of student caregivers in 22 school pairs (2017 survey, N = 6,070; 2018 survey, N = 6,507). We estimated the incidence of laboratory-confirmed influenza hospitalization from 2011 to 2018 using surveillance data from school district zip codes. We analyzed student absenteeism data from 2011 to 2018 from each district (N = 42,487,816 student-days). To account for pre-intervention differences between districts, we estimated difference-in-differences (DID) in influenza hospitalization incidence and absenteeism rates using generalized linear and log-linear models with a population offset for incidence outcomes. Prior to the SLIV intervention, the median household income was $51,849 in the intervention site and $61,596 in the comparison site. The population in each site was predominately white (41% in the intervention site, 48% in the comparison site) and/or of Hispanic or Latino ethnicity (26% in the intervention site, 33% in the comparison site). The number of students vaccinated by the SLIV intervention ranged from 7,502 to 10,106 (22%–28% of eligible students) each year. During the intervention, influenza vaccination coverage among elementary students was 53%–66% in the comparison district. Coverage was similar between the intervention and comparison districts in influenza seasons 2014–2015 and 2015–2016 and was significantly higher in the intervention site in seasons 2016–2017 (7%; 95% CI 4, 11; p < 0.001) and 2017–2018 (11%; 95% CI 7, 15; p < 0.001). During seasons when vaccination coverage was higher among intervention schools and the vaccine was moderately effective, there was evidence of statistically significant indirect effects: The DID in the incidence of influenza hospitalization per 100,000 in the intervention versus comparison site was −17 (95% CI −30, −4; p = 0.008) in 2016–2017 and −37 (95% CI −54, −19; p < 0.001) in 2017–2018 among non-elementary-school-aged individuals and −73 (95% CI −147, 1; p = 0.054) in 2016–2017 and −160 (95% CI −267, −53; p = 0.004) in 2017–2018 among adults 65 years or older. The DID in illness-related school absences per 100 school days during the influenza season was −0.63 (95% CI −1.14, −0.13; p = 0.014) in 2016–2017 and −0.80 (95% CI −1.28, −0.31; p = 0.001) in 2017–2018. Limitations of this study include the use of an observational design, which may be subject to unmeasured confounding, and caregiver-reported vaccination status, which is subject to poor recall and low response rates. A city-wide SLIV intervention in a large, diverse urban population was associated with a decrease in the incidence of laboratory-confirmed influenza hospitalization in all age groups and a decrease in illness-specific school absence rate among students in 2016–2017 and 2017–2018, seasons when the vaccine was moderately effective, suggesting that the intervention produced indirect effects. Our findings suggest that in populations with moderately high background levels of influenza vaccination coverage, SLIV programs are associated with further increases in coverage and reduced influenza across the community.

Shigella causes an estimated 500000 enteric illnesses in the United States annually, but the association with socioeconomic factors is unclear. We examined possible epidemiologic associations between shigellosis and poverty using 2004–2014 Foodborne Diseases Active Surveillance Network (FoodNet) data. Shigella cases (n = 21246) were geocoded, linked to Census tract data from the American Community Survey, and categorized into 4 poverty and 4 crowding strata. For each stratum, we calculated incidence by sex, age, race/ethnicity, and FoodNet site. Using negative binomial regression, we estimated incidence rate ratios (IRRs) comparing the highest to lowest stratum. Annual FoodNet Shigella incidence per 100000 population was higher among children Shigella infections are epidemiologically associated with poverty, and increased incidence rates are observed among young children, blacks, and Hispanics.

Background: It is estimated that vaccinating 50-70% of school-aged children for influenza can produce population-wide indirect effects. We evaluated a city-wide, school-located influenza vaccination (SLIV) intervention that aimed to increase influenza vaccination coverage. The intervention was implemented in over 95 pre-schools and elementary schools in northern California from 2014 to 2018. Using a matched prospective cohort design, we estimated intervention impacts on student influenza vaccination coverage, school absenteeism, and community-wide indirect effects on laboratory-confirmed influenza hospitalizations. Methods and Findings: We used a multivariate matching algorithm to identify a nearby comparison school district with similar pre-intervention characteristics and matched schools in each district. To measure student influenza vaccination, we conducted cross-sectional surveys of student caregivers in 22 school pairs (2016 survey N = 6,070; 2017 survey N = 6,507). We estimated the incidence of laboratory-confirmed influenza hospitalization from 2011-2018 using surveillance data from school district zip codes. We analyzed student absenteeism data from 2011-2018 from each district (N = 42,487,816 student-days). To account for pre-intervention differences between districts, we estimated difference-in-differences (DID) in influenza hospitalization incidence and absenteeism rates using generalized linear and log-linear models with a population offset for incidence outcomes. The number of students vaccinated by the SLIV intervention ranged from 7,502 to 10,106 (22-28% of eligible students) each year. During the intervention, influenza vaccination coverage among elementary students was 53-66% in the comparison district. Coverage was similar between the intervention and comparison districts in 2014-15 and 2015-16 and was significantly higher in the intervention site in 2016-17 (7% 95% CI 4, 11) and 2017-18 (11% 95% CI 7, 15). During seasons when vaccination coverage was higher among intervention schools and the vaccine was moderately effective, there was evidence of statistically significant indirect effects: adjusting for pre-intervention differences between districts, the reduction in influenza hospitalizations in the intervention site was 76 (95% CI 20, 133) in 2016-17 and 165 (95% CI 86, 243) in 2017-18 among non-elementary school aged individuals and 327 (5, 659) in 2016-17 and 715 (236, 1195) in 2017-18 among adults 65 years or older. The reduction in illness-related school absences during influenza season was 3,538 (95% CI 709, 6,366) in 2016-17 and 8,249 (95% CI 3,213, 13,285) in 2017-18. Limitations of this study include the use of an observational design, which may be subject to unmeasured confounding, and caregiver-reported vaccination status, which is subject to poor recall and low response rates. Conclusion: A city-wide SLIV intervention in a large, diverse urban population decreased the incidence of laboratory-confirmed influenza hospitalization in all age groups and decreased illness-specific school absence rates among students during seasons when the vaccine was moderately effective, suggesting that the intervention produced indirect effects. Our findings suggest that in populations with moderately high background levels of influenza vaccination coverage, SLIV programs can further increase coverage and reduce influenza across communities.

Background: The relationships between socioeconomic status and domestically acquired salmonellosis and leading Salmonella serotypes are poorly understood. Methods: We analyzed surveillance data from laboratory-confirmed cases of salmonellosis from 2010–2016 for all 10 Foodborne Disease Active Surveillance Network (FoodNet) sites, having a catchment population of 47.9 million. Case residential data were geocoded, linked to census tract poverty level, and then categorized into 4 groups according to census tract poverty level. After excluding those reporting international travel before illness onset, age-specific and age-adjusted salmonellosis incidence rates were calculated for each census tract poverty level, overall and for each of the 10 leading serotypes. Results: Of 52 821geocodable Salmonella infections (>96%), 48 111 (91.1%) were domestically acquired. Higher age-adjusted incidence occurred with higher census tract poverty level (P < .001; relative risk for highest [≥20%] vs lowest [<5%] census tract poverty level, 1.37). Children <5 years old had the highest relative risk (2.07). Although this relationship was consistent by race/ethnicity and by serotype, it was not present in 5 FoodNet sites or among those aged 18–49 years. Conclusion: Children and older adults living in higher-poverty census tracts have had a higher incidence of domestically acquired salmonellosis. There is a need to understand socioeconomic status differences for risk factors for domestically acquired salmonellosis by age group and FoodNet site to help focus prevention efforts.