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Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research. In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research. We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing. We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations-wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%). Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.

In 2023, the World Health Organization (WHO) revised its guidelines for management of severe acute malnutrition (SAM). The revised guidelines include a focus on infants at risk of poor growth and development. The guideline identifies evaluation of routine antibiotics for these infants as a priority research area. We pooled data from two large randomized controlled trials evaluating azithromycin for prevention of infant mortality in Burkina Faso to assess whether azithromycin reduces mortality or wasting in this subgroup. Infants in the two trials were 1-12 weeks of age at enrollment. Infants were considered at risk of poor risk of growth and development per WHO: underweight (weight-for-age Z-score, WAZ < -2), wasted (weight-for-length Z-score, WLZ < -2), or MUAC < 11.0 cm among infants ≥6 weeks of age. Infants were randomized to a single oral (20 mg/kg) dose of azithromycin or matching placebo and were followed until 6 months of age. We evaluated vital status, underweight (WAZ < -2), wasting (WLZ < -2), and stunting (length-for-age Z-score, LAZ) at 6 months among infants at risk of poor growth and development based on WHO single measurement criteria. A total of 54,709 infants were enrolled in the two trials. Of these, 9,728 were at risk of poor growth and development based on baseline WAZ (N = 5,385), WLZ (N = 6,022), or MUAC (N = 1,541). We found no evidence of a difference in mortality (1.3% vs 1.1%, odds ratio, OR, 1.19, 95% confidence interval, CI, 0.82 to 1.72) or wasting (20.6% vs 20.2%, OR 1.03, 95% CI 0.92 to 1.14) at 6 months among infants receiving azithromycin versus placebo. In infants aged 1-12 weeks at risk of poor growth and development, we do not have evidence that single dose azithromycin reduces mortality or improves growth outcomes. ClinicalTrials.gov NCT03682654 and NCT03676764.

Antibiotic use during early infancy has been linked to childhood obesity in high-income countries. We evaluated whether a single oral dose of azithromycin administered during infant-well visits led to changes in infant growth outcomes at 6 months of age in a setting with a high prevalence of undernutrition in rural Burkina Faso. Infants were enrolled from September 25, 2019, until October 22, 2022, in a randomized controlled trial designed to evaluate the efficacy of a single oral dose of azithromycin (20 mg/kg) compared to placebo when administered during well-child visits for prevention of infant mortality. The trial found no evidence of a difference in the primary endpoint. This paper presents prespecified secondary anthropometric endpoints including weight gain (g/day), height change (mm/day), weight-for-age Z-score (WAZ), weight-for-length Z-score (WLZ), length-for-age Z-score (LAZ), and mid-upper arm circumference (MUAC). Infants were eligible for the trial if they were between 5 and 12 weeks of age, able to orally feed, and their families were planning to remain in the study area for the duration of the study. Anthropometric measurements were collected at enrollment (5 to 12 weeks of age) and 6 months of age. Among 32,877 infants enrolled in the trial, 27,298 (83%) were followed and had valid anthropometric measurements at 6 months of age. We found no evidence of a difference in weight gain (mean difference 0.03 g/day, 95% confidence interval (CI) -0.12 to 0.18), height change (mean difference 0.004 mm/day, 95% CI -0.05 to 0.06), WAZ (mean difference -0.004 SD, 95% CI -0.03 to 0.02), WLZ (mean difference 0.001 SD, 95% CI -0.03 to 0.03), LAZ (mean difference -0.005 SD, 95% CI -0.03 to 0.02), or MUAC (mean difference 0.01 cm, 95% CI -0.01 to 0.04). The primary limitation of the trial was that measurements were only collected at enrollment and 6 months of age, precluding assessment of shorter-term or long-term changes in growth. Single-dose azithromycin does not appear to affect weight and height outcomes when administered during early infancy. ClinicalTrials.gov NCT03676764.

As the epidemiological transition progresses throughout sub-Saharan Africa, life lived with diseases is an increasingly important part of a population’s burden of disease. The burden of disease of climate-sensitive health outcomes is projected to increase considerably within the next decades. Objectively measured, reliable population health data is still limited and is primarily based on perceived illness from recall. Technological advances like non-invasive, consumer-grade wearable devices may play a vital role in alleviating this data gap and in obtaining insights on the disease burden in vulnerable populations, such as heat stress on human cardiovascular response. The overall goal of this study is to investigate whether consumer-grade wearable devices are an acceptable, feasible and valid means to generate data on the individual level in low-resource contexts. Three hundred individuals are recruited from the two study locations in the Nouna health and demographic surveillance system (HDSS), Burkina Faso, and the Siaya HDSS, Kenya. Participants complete a structured questionnaire that comprises question items on acceptability and feasibility under the supervision of trained data collectors. Validity will be evaluated by comparing consumer-grade wearable devices to research-grade devices. Furthermore, we will collect demographic data as well as the data generated by wearable devices. This study will provide insights into the usage of consumer-grade wearable devices to measure individual vital signs in low-resource contexts, such as Burkina Faso and Kenya. Vital signs comprising activity (steps), sleep (duration, quality) and heart rate (hr) are important measures to gain insights on individual behavior and activity patterns in low-resource contexts. These vital signs may be associated with weather variables—as we gather them from weather stations that we have setup as part of this study to cover the whole Nouna and Siaya HDSSs—in order to explore changes in behavior and other variables, such as activity, sleep, hr, during extreme weather events like heat stress exposure. Furthermore, wearable data could be linked to health outcomes and weather events. As a result, consumer-grade wearables may serve as a supporting technology for generating reliable measurements in low-resource contexts and investigating key links between weather occurrences and health outcomes. Thus, wearable devices may provide insights to better inform mitigation and adaptation interventions in these low-resource settings that are direly faced by climate change-induced changes, such as extreme weather events.

Background Delays in care-seeking for childhood illness may lead to more severe outcomes. We evaluated whether community distance from a primary healthcare facility was associated with decreased healthcare utilization in a rural district of northwestern Burkina Faso. Methods We conducted passive surveillance of all government-run primary healthcare facilities in Nouna District, Burkina Faso from March 1 through May 31, 2020. All healthcare visits for children under 5 years of age were recorded on a standardized form for sick children. We recorded the age, sex, and community of residence of the child as well as any diagnoses and treatments administered. We calculated healthcare utilization per 100 child-months by linking the aggregate number of visits at the community level to the community’s population of children under 5 months per a census that was conducted from August 2019 through February 2020. We calculated the distance between each community and its corresponding healthcare facility and assessed the relationship between distance and the rate of healthcare utilization. Results In 226 study communities, 12,676 primary healthcare visits were recorded over the three-month period. The median distance between the community and primary healthcare facility was 5.0 km (IQR 2.6 to 6.9 km), and median number of healthcare visits per 100 child-months at the community level was 6.7 (IQR 3.7 to 12.3). The rate of primary healthcare visits declined with increasing distance from clinic (Spearman’s rho − 0.42, 95% CI − 0.54 to − 0.31, P  < 0.0001). This relationship was similar for cause-specific clinic visits (including pneumonia, malaria, and diarrhea) and for antibiotic prescriptions. Conclusions We documented a distance decay effect between community distance from a primary healthcare facility and the rate of healthcare visits for children under 5. Decreasing distance-related barriers, for example by increasing the number of facilities or targeting outreach to more distant communities, may improve healthcare utilization for young children in similar settings.

Background The risk of malaria transmission varies between rural and urban areas. Environmental characteristics and habitat structure can explain this variation. Understanding these factors is crucial for the informed selection of existing and new vector control tools. This study investigated how housing and household characteristics affect vector abundance and malaria incidence in a semi-urban and rural setting of Burkina Faso. Methods CDC light traps were used to sample indoor mosquitoes from July to October 2021 in 355 randomly selected houses in semi-urban and rural areas of the Nouna health district. A digital data collection application was used to record information on occupants, housing structure, and household characteristics. Indoor temperature was monitored with a wall thermometer during the night of mosquito collection. Mosquitoes were morphologically sorted and identified by Polymerase Chain Reaction. Poisson and logistic linear models were used to assess the effects of house structure and household characteristics on indoor mosquito abundance, mosquito infection, and human malaria cases. Results A total of 22,863 mosquitoes were collected, the most abundant of which were Anopheles including Anopheles coluzzii , Anopheles gambiae sensu stricto, Anopheles arabiensis . In the rural site, minor vectors such as  Anopheles nili , Anopheles funestus, and Anopheles pharoensis were found. Mosquito abundance, the number of infected mosquitoes, and the presence of human malaria cases didn't vary significantly according to wall type, roof type, the presence of breeding sites, and the use of LLINs. However, the vegetation around the houses was positively associated with mosquito abundance [RR: 2.5; CI (1.43–4.15); p < 0.001], vector infection [RR = 2.5; CI (1.74–3.33); p < 0.001], and the presence of malaria cases [RR: 1.4; CI (1.03–2.0); p = 0.048]. The presence of children under five years of age [RR: 1.52; CI (1.25–1.84); p < 0.001], female householder [RR: 1.23; CI (1.02–2.78); p < 0.001] were also significantly associated with the human malaria cases. Conclusion The household environment, such as vegetation around houses, appears to increase the risk of malaria transmission, while building materials have a smaller effect, in semi urban and rural areas of Burkina Faso. In addition to prophylaxis and medication, malaria control strategies must strengthen environmental management to keep vector populations away from human dwellings.

To examine how child mortality among children aged 1-59 months varies by asset-based wealth status in rural Burkina Faso, and to assess the interaction between mass azithromycin (AZ) distribution and wealth status on child mortality at both the household and community levels. We used data from a cluster-randomized trial and population census data on household characteristics and assets. A wealth index score for each household, used to classify the population by wealth, was generated using principal component analysis. We used the Relative Index of Inequality (RII), the Slope Index of Inequality (SII), and the concentration index to assess wealth-related inequalities in mortality, and the Gini Index to assess variability in child mortality across households and communities. Poisson regression models were used, with person-time at risk included as an offset, and robust standard error to estimate changes in mortality rates by wealth and treatment arm. Interaction was assessed on both the multiplicative and additive scales. Mortality declined with increasing wealth at both the household and community levels, with a significant gradient at the community level (RII = 1.17, 95% CI: 1.05-1.29; SII = 2.3 per 1,000 person-years, 95% CI: 0.2-4.4), reflecting higher mortality among the poorest. The effect of AZ did not vary significantly by wealth index, and changes in mortality rates across wealth levels were similar between the two treatment arms. There was no evidence of a statistically significant interaction between AZ and asset-based wealth on either the multiplicative or additive scale at the household or cluster level. Our findings demonstrate a wealth gradient in child mortality, with the highest mortality rates observed among households and communities in the lowest wealth quintiles. These disparities were consistent across both AZ-treated and placebo groups, suggesting that the role of AZ in health disparities may be limited to addressing gaps in treatment access rather than broader wealth-related disparities. While the study may have been underpowered to detect modest interaction effects, AZ appeared to offer similar benefits across economically diverse communities, with no evidence suggesting enhanced benefits for disadvantaged communities or for prioritizing treatment based on wealth status. Further work is needed to address the wealth-related disparities in child mortality in these communities. ClinicalTrials.gov NCT03676764.

Background While Seasonal Malaria Chemoprevention (SMC) has been adopted as a malaria control strategy in regions with seasonal transmission, continued monitoring and evaluation of its effectiveness across diverse ecological, epidemiological, and healthcare settings remain critical for optimizing the intervention. This study aims to assess the ongoing population-level impact of SMC under routine programme conditions by evaluating rates of uncomplicated and severe malaria following four rounds of administration. Methods A pre-post analysis was conducted using real-world surveillance data from clinic visits in 285 villages in Nouna District, Burkina Faso, along with National Malaria Control Programme data on SMC administration. Estimates of the population used for person-time calculations were derived from a census conducted as part of a randomized controlled trial. Malaria rates for children under 5 were analyzed for each epidemiological week in 2021, for each health post in the study area. Negative binomial regression models were used, with person-time at risk used as an offset and standard errors clustered by health post, to obtain incidence rate ratios (IRRs) and rate differences. Changes in diagnoses were estimated from the administration weeks to each of the three weeks post- administration within the same population. Injury rates were used as a negative control outcome to assess potential unmeasured confounding. Results Although SMC was administered during peak malaria transmission weeks within each cycle, both uncomplicated and severe malaria rates remained high through December, following the fourth and final round of SMC. There was a substantial reduction in infection rates in the 3 weeks post SMC, with gradual increases in rates across the three weeks. The rates of uncomplicated and severe malaria per 1000 person-weeks in the administration weeks were 8.5 (95% CI 7.0 to 10.1) and 0.31 (95% CI 0.22 to 0.40), respectively. Uncomplicated malaria rates were lower by 41%, 95%CI (31–50%), 34% (23–43%) and 22% (12–31%) in the first, second and third weeks after administration, respectively. Severe malaria rates declined by 47% (21–64%), 47% (31–59%) and 34% (17–47%) in the three weeks post-administration. Injury rates, the negative control outcome, did not change significantly across the three weeks. Conclusion In programme settings, at the population level, SMC administration was associated with a substantial reduction in uncomplicated and severe malaria, though this effect was limited to the immediate weeks following administration. The gradual increase in malaria rates by the third week suggests a shorter duration of protection than previously observed. Extending the areas where 5 rounds of distribution occur may be necessary to effectively prevent malaria infections in regions with a longer transmission season. Regular evaluation of local malaria trends and impact of SMC can help further tailor and optimize SMC programmes for specific regional contexts.

Objective To assess the benefits of Seasonal Malaria Chemoprevention (SMC)—the monthly administration of sulfadoxine-pyrimethamine and amodiaquine—beyond malaria prevention in real-world program settings. Methods We conducted a pre-post comparison of non-malarial diagnoses (pneumonia, diarrhea, acute malnutrition) and antibiotic prescription rates during SMC administration weeks versus a three-week post-intervention period in rural Burkina Faso. Data was obtained from clinic surveillance at 51 health facilities, a population-based census, and National Malaria Control Program data on SMC timing. Poisson regression models with person-weeks as an offset and standard errors clustered by health post estimated changes in rates. Interaction terms assessed variation across SMC cycles. Positive (malaria diagnoses, antimalarial prescriptions) and negative (injury) control outcomes were used to evaluate potential unmeasured confounding. Results Compared to administration weeks, modest declines were observed in pneumonia, diarrhea, and acute malnutrition diagnoses, as well as in antibiotic prescription rates during the post-SMC period. Absolute reductions were 0.7 (95% CI: 0.3–1.0), 0.2 (95% CI: 0.1–0.4), 0.05 (95% CI: 0.001–0.09), and 0.90 (95% CI: 0.4–1.4) per 1,000 person-weeks, respectively ( corresponding IRRs: 0.86 , 0.83 , 0.71 , and 0.88 ). Positive control outcomes also declined, with malaria diagnoses and antimalarial prescriptions decreasing by 3.7 (95% CI: 2.6–4.8) and 3.6 (95% CI: 2.5–4.7) per 1,000 person-weeks ( IRRs: 0.62 and 0.63 ). Injury rates (negative control) remained stable (0.02; 95% CI: −0.03 to 0.07). Reductions varied across SMC cycles and were most pronounced following the final round. Conclusion SMC may have additional benefits beyond malaria prevention, including reductions in common pediatric infections and subsequent routine antibiotic use. Clinical trial Not applicable.

Background High ambient air temperatures in Africa pose significant health and behavioral challenges in populations with limited access to cooling adaptations. The built environment can exacerbate heat exposure, making passive home cooling adaptations a potential method for protecting occupants against indoor heat exposure. Methods We are conducting a 2-year community-based stratified cluster randomized controlled trial (cRCT) implementing sunlight-reflecting roof coatings, known as “cool roofs,” as a climate change adaptation intervention for passive indoor home cooling. Our primary research objective is to investigate the effects of cool roofs on health, indoor climate, economic, and behavioral outcomes in rural Burkina Faso. This cRCT is nested in the Nouna Health and Demographic Surveillance System (HDSS), a population-based dynamic cohort study of all people living in a geographically contiguous area covering 59 villages, 14305 households and 28610 individuals. We recruited 1200 participants, one woman and one man, each in 600 households in 25 villages in the Nouna HDSS. We stratified our sample by (i) village and (ii) two prevalent roof types in this area of Burkina Faso: mud brick and tin. We randomized the same number of people (12) and homes (6) in each stratum 1:1 to receiving vs. not receiving the cool roof. We are collecting outcome data on one primary endpoint - heart rate, (a measure of heat stress) and 22 secondary outcomes encompassing indoor climate parameters, blood pressure, body temperature, heat-related outcomes, blood glucose, sleep, cognition, mental health, health facility utilization, economic and productivity outcomes, mosquito count, life satisfaction, gender-based violence, and food consumption. We followed all participants for 2 years, conducting monthly home visits to collect objective and subjective outcomes. Approximately 12% of participants ( n  = 152) used smartwatches to continuously measure endpoints including heart rate, sleep and activity. Discussion Our study demonstrates the potential of large-scale cRCTs to evaluate novel climate change adaptation interventions and provide evidence supporting investments in heat resilience in sub-Saharan Africa. By conducting this research, we will contribute to better policies and interventions to help climate-vulnerable populations ward off the detrimental effects of extreme indoor heat on health. Trial registration German Clinical Trials Register (DRKS) DRKS00023207. Registered on April 19, 2021.