Validity of Self-Report for Ascertaining HIV Status Among Circular Migrants and Permanent Residents in South Africa: A Cross-Sectional, Population-Based Analysis.

While expanded HIV testing is needed in South Africa, increasing accurate self-report of HIV status is an essential parallel goal in this highly mobile population. If self-report can ascertain true HIV-positive status, persons with HIV (PWH) could be linked to life-saving care without the existing delays required by producing medical records or undergoing confirmatory testing, which are especially burdensome for the country's high prevalence of circular migrants. We used Wave 1 data from The Migration and Health Follow-Up Study, a representative adult cohort, including circular migrants and permanent residents, randomly sampled from the Agincourt Health and Demographic Surveillance System in a rural area of Mpumalanga Province. Within the analytic sample (n = 1,918), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of self-report were calculated with dried blood spot (DBS) HIV test results as the standard. Among in-person participants (n = 2,468), 88.8% consented to DBS-HIV testing. HIV prevalence was 25.3%. Sensitivity of self-report was 43.9% (95% CI: 39.5-48.5), PPV was 93.4% (95% CI: 89.5-96.0); specificity was 99.0% (95% CI: 98.3-99.4) and NPV was 83.9% (95% CI: 82.8-84.9). Self-report of an HIV-positive status was predictive of true status for both migrants and permanent residents in this high-prevalence setting. Persons who self-reported as living with HIV were almost always truly positive, supporting a change to clinical protocol to immediately connect persons who say they are HIV-positive to ART and counselling. However, 56% of PWH did not report as HIV-positive, highlighting the imperative to address barriers to disclosure.

Epidemiology of chronic multimorbidity and temporary migration in a rural South African community in health transition: A cross-sectional population-based analysis.

Introduction: In sub-Saharan African settings, the increasing non-communicable disease mortality is linked to migration, which disproportionately exposes sub-populations to risk factors for co-occurring HIV and NCDs. Methods: We examined the prevalence, patterns, and factors associated with two or more concurrent diagnoses of chronic diseases (i.e., multimorbidity) among temporary within-country migrants. Employing a cross-sectional design, our study sample comprised 2144 residents and non-residents 18-40 years interviewed and with measured biomarkers in 2018 in Wave 1 of the Migrant Health Follow-up Study (MHFUS), drawn from the Agincourt Health and Demographic Surveillance System (AHDSS) in rural north-eastern South Africa. We used modified Poisson regression models to estimate the association between migration status and prevalent chronic multimorbidity conditional on age, sex, education, and healthcare utilisation. Results: Overall, 301 participants (14%; 95% CI 12.6-15.6), median age 31 years had chronic multimorbidity. Multimorbidity was more prevalent among non-migrants (14.6%; 95% CI 12.8-16.4) compared to migrants (12.8%; 95% CI 10.3-15.7). Non-migrants also had the greatest burden of dual-overlapping chronic morbidities, such as HIV-obesity 5.7%. Multimorbidity was 2.6 times as prevalent (PR 2.65. 95% CI 2.07-3.39) among women compared to men. Among migrants, men, and individuals with secondary or tertiary education manifested lower prevalence of two or more conditions. Discussion: In a rural community with colliding epidemics, we found low but significant multimorbidity driven by a trio of conditions: HIV, hypertension, and obesity. Understanding the multimorbidity burden associated with early adulthood exposures, including potential protective factors (i.e., migration coupled with education), is a critical first step towards improving secondary and tertiary prevention for chronic disease among highly mobile marginalised sub-populations.

The impact of COVID-19 on a cohort of origin residents and internal migrants from South Africa's rural northeast.

South Africa has a large temporary migrant population with people commonly moving to metropolitan areas to access employment, while maintaining links with their rural origin households. The COVID-19 pandemic has impacted patterns of movement, livelihoods and health seeking, and the effects on internal, temporary migrants are unclear. Using longitudinal data spanning 2018 to 2020, this paper employs descriptive statistics and regression analyses to assess the impacts of COVID-19 on a cohort of 2971 persons aged 18-40 at baseline, both residents and migrants, from a rural district in South Africa's northeast. In contrast with 2018-2019, in 2020 the share of rural residents initiating a migration decreased by 11 percentage points (p<0.001), while the share of temporary migrants returning to origin households increased by 5 percentage points (p<0.001). Study participants who were continuing migrants reported fewer job losses in comparison with rural-stayers, while 76% of return migrants who were employed in 2019 were no longer employed in 2020. Further, among those who did not experience food shortages in 2019, rural-stayers had 1.42 times the odds of continuing migrants of suffering shortages in 2020. In 2020 health service use in the cohort decreased overall, with return migrants having still lower odds of utilising health services. The results highlight the differential geographic and socioeconomic manifestations of the pandemic, with worsening socioeconomic circumstances observed for rural-staying (disproportionately female) and returning populations, while continuing migrants fared relatively better. It is vital that a COVID-19 response considers the potentially heterogeneous impact of the pandemic on mobile and stable populations. Policy responses may include targeting migrants at their destinations in health promotion of COVID-19 messaging, and strengthening health care and social support in origin communities in recognition that these areas receive return migrants into their catchment population.

Migrant health penalty: evidence of higher mortality risk among internal migrants in sub-Saharan Africa.

Background: Despite the greater attention given to international migration, internal migration accounts for the majority of movements globally. However, research on the effects of internal migration on health is limited, with this relationship examined predominantly in urban settings among working-age adults, neglecting rural populations and younger and older ages.Objectives: Using longitudinal data from 29 mostly rural sub-Saharan African Health and Demographic Surveillance Systems (HDSS), this study aims to explore life-course differences in mortality according to migration status and duration of residence.MethodsCox proportional hazards models are employed to analyse the relationship between migration and mortality in the 29 HDSS areas. The analytical sample includes 3 836,173 people and the analysis spans 25 years, from 1990 to 2015. We examine the risk of death by sex across five broad age groups (from ages 1 to 80), and consider recent and past in- and return migrants.Results: In-migrants have a higher risk of mortality compared to permanent rural residents, with return migrants at greater risk than in-migrants across all age-groups. Female migrants have lower survival chances than males, with greater variability by age. Risk of dying is highest among recent return migrant females aged 30-59: 1.86 (95% CI 1.69-2.06) times that of permanent residents. Only among males aged 15-29 who move to urban areas is there evidence of a 'healthy migrant' effect (HR = 0.62, 95% CI 0.51-0.77). There is clear evidence of an adaptation effect across all ages, with the risk of mortality reducing with duration following migration.Conclusions: Findings suggest that adult internal migrants, particularly females, suffer greater health disadvantages associated with migration. Policy makers should focus on improving migrant's interface with health services, and support the development of health education and promotion interventions to create awareness of localised health risks for migrants.

Internal migration and health in South Africa: determinants of healthcare utilisation in a young adult cohort.

BACKGROUND: In South Africa, human geographic mobility is high as people engage in both permanent and temporary relocation, predominantly from rural to urban areas. Such mobility can compromise healthcare access and utilisation. The objective of this paper is to explore healthcare utilisation and its determinants in a cohort of internal migrants and permanent residents (non-migrants) originating from the Agincourt sub-district in South Africa's rural northeast. METHODS: A 5-year cohort study of 3800 individuals aged 18 to 40 commenced in 2017. Baseline data have been collected from 1764 Agincourt residents and 1334 temporary, mostly urban-based, migrants, and are analysed using bivariate analyses, logistic and multinomial regression models, and propensity score matching analysis. RESULTS: Health service utilisation differs sharply by migrant status and sex. Among those with a chronic condition, migrants had 0.33 times the odds of non-migrants to have consulted a health service in the preceding year, and males had 0.32 times the odds of females of having used health services. Of those who utilised services, migration status was further associated with the type of healthcare utilised, with 97% of non-migrant rural residents having accessed government facilities, while large proportions of migrants (31%) utilised private health services or consulted traditional healers (25%) in migrant destinations. The multinomial logistic regression analysis indicated that, in the presence of controls, migrants had 8.12 the relative risk of non-migrants for utilising private healthcare (versus the government-services-only reference category), and 2.40 the relative risk of non-migrants for using a combination of public and private sector facilities. These findings of differential utilisation hold under statistical adjustment for relevant controls and for underlying propensity to migrate. CONCLUSIONS: Migrants and non-migrants in the study population in South Africa were found to utilise health services differently, both in overall use and in the type of healthcare consulted. The study helps improve upon the limited stock of knowledge on how migrants interface with healthcare systems in low and middle-income country settings. Findings can assist in guiding policies and programmes to be directed more effectively to the populations most in need, and to drive locally adapted approaches to universal health coverage.

Health and demographic surveillance systems in low- and middle-income countries: history, state of the art and future prospects.

Health and Demographic Surveillance Systems (HDSS) have been developed in several low- and middle-income countries (LMICs) in Africa and Asia. This paper reviews their history, state of the art and future potential and highlights substantial areas of contribution by the late Professor Peter Byass.Historically, HDSS appeared in the second half of the twentieth century, responding to a dearth of accurate population data in poorly resourced settings to contextualise the study of interventions to improve health and well-being. The progress of the development of this network is described starting with Pholela, and progressing through Gwembe, Balabgarh, Niakhar, Matlab, Navrongo, Agincourt, Farafenni, and Butajira, and the emergence of the INDEPTH Network in the early 1990'sThe paper describes the HDSS methodology, data, strengths, and limitations. The strengths are particularly their temporal coverage, detail, dense linkage, and the fact that they exist in chronically under-documented populations in LMICs where HDSS sites operate. The main limitations are generalisability to a national population and a potential Hawthorne effect, whereby the project itself may have changed characteristics of the population.The future will include advances in HDSS data harmonisation, accessibility, and protection. Key applications of the data are to validate and assess bias in other datasets. A strong collaboration between a national HDSS network and the national statistics office is modelled in South Africa and Sierra Leone, and it is possible that other low- to middle-income countries will see the benefit and take this approach.