Prevalence and socio-economic determinates of food insecurity in Veterans: findings from National Health and Nutrition Examination Survey.

OBJECTIVE: To determine predictors of the association between being a Veteran and adult food security, as well as to examine the relation of potential covariates to this relationship. DESIGN: Data collected during 2011-2012, 2013-2014 and 2015-2016 National Health and Nutrition Examination Survey (NHANES) were pooled for analyses. Veterans (self-reported) were matched to non-Veterans on age, race/ethnicity, sex and education. Adjusted logistic regression was used to determine the odds of Veterans having high food security v. the combination of marginal, low and very low food security compared with non-Veterans. SETTING: 2011-2012, 2013-2014 and 2015-2016 NHANES. PARTICIPANTS: 1227 Veterans; 2432 non-Veterans. RESULTS: Veteran status had no effect on the proportion of food insecurities between Veterans and non-Veterans reporting high (Veterans v. non-Veteran: 79 % v. 80 %), marginal (9 % v. 8 %), low (5 % v. 6 %) and very low (8 % v. 6 %) food security (P = 0·11). However, after controlling for covariates, Veterans tended to be less likely to have high food security (OR: 0·82 (95 % CI 0·66, 1·02), P = 0·07). Further, non-Hispanic White Veterans (OR: 0·72 (95 % CI 0·55, 0·95), P = 0·02) and Veterans completing some college (OR: 0·71 (95 % CI 0·50, 0·99), P < 0·05) were significantly less likely to experience high food security compared with non-Veterans. CONCLUSION: This study supports previous research findings that after controlling for covariates, Veterans tend to be less likely to have high food security. It also highlights ethnicity and level of education as important socio-economic determinates of food security status in Veterans.

Performance of HIV rapid testing algorithm in Nigeria: Findings from a household-based Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS).

BACKGROUND: The Nigeria AIDS Indicator and Impact Survey (NAIIS), a cross-sectional household survey, was conducted in 2018 with primary objectives to estimate HIV prevalence, HIV-1 incidence, and status of UNAIDS 90-90-90 cascade. We conducted retrospective analysis of the performance of HIV rapid tests and the national HIV testing algorithm used in Nigeria. METHODS: The national algorithm included Determine HIV-1/2 as test 1 (T1), Unigold HIV-1/2 as test 2 (T2), and StatPak HIV-1/2 as the tie-breaker test (T3). Individuals reactive with T1 and either T2 or T3 were considered HIV-positive. HIV-positive specimens from the algorithm were further confirmed for the survey using supplemental test Geenius HIV-1/2. If Geenius did not confirm HIV-positive status, HIV-1 Western blot was performed. We calculated the concordance between tests and positive predictive value (PPV) of the algorithm on unweighted data. RESULTS: Of 204,930 participants (ages ≥18 months) 5,103 (2.5%) were reactive on T1. Serial testing of T1 reactive specimens with T2 or if needed by tiebreaker T3 identified 2958 (1.44%) persons as HIV-positive. Supplemental testing confirmed 2,800 (95%) as HIV-positive (HIV-1 = 2,767 [98.8%]; HIV-2 = 5 [0.2%]; dual infections = 22 [0.8%]). Concordance between T1 and T2 was 56.6% while PPV of the national algorithm was 94.5%. CONCLUSIONS: Our results show high discordant rates and poor PPV of the national algorithm with a false-positive rate of about 5.5% in the NAIIS survey. Considering our findings have major implications for HIV diagnosis in routine HIV testing services, additional evaluation of testing algorithm is warranted in Nigeria.

Lessons From Rapid Field Implementation of an HIV Population-Based Survey in Nigeria, 2018.

BACKGROUND: The need for accurate HIV annual program planning data motivated the compressed timeline for the 2018 Nigerian HIV/AIDS Indicator and Impact Survey (NAIIS). The survey team used stakeholder cooperation and responsive design, using survey process and paradata to refine survey implementation, to quickly collect high-quality data. We describe processes that led to generation of data for program and funding decisions, ensuring HIV services were funded in 2019. SETTING: Nigeria is the most populous country in Africa, with approximately 195 million people in 36 states and the Federal Capital Territory. Challenges include multiple security threats, poor infrastructure, seasonal rains, and varied health system capacity. METHODS: Stakeholders worked together to plan and implement NAIIS. Methods from other population-based HIV impact assessments were modified to meet challenges and the compressed timeline. Data collection was conducted in 6 webs. Responsive design included reviewing survey monitoring paradata and laboratory performance. Costs required to correct data errors, for example, staff time and transportation, were tracked. RESULTS: NAIIS data collection was completed in 23 weeks, ahead of the originally scheduled 24 weeks. Responsive design identified and resolved approximately 68,000 interview errors, affecting approximately 62,000 households, saving about US$4.4 million in costs. Biweekly field laboratory test quality control improved from 50% to 100% throughout NAIIS. CONCLUSIONS: Cooperation across stakeholders and responsive design ensured timely release of NAIIS results and informed planning for HIV epidemic control in Nigeria. Based on NAIIS results, funds were provided to place an additional 500,000 HIV-positive Nigerians on antiretroviral therapy by the end of 2020, pushing Nigeria toward epidemic control.