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Mobile Health (mHealth) presents the potential to facilitate healthcare and improve the quality of life if successful pilot projects are scaled up and sustainable. However, the persistent termination of mHealth at the pilot phase challenges its potential in developing countries. Existing research suggests an absence of understanding of these phenomena for two reasons. First, literature is scarce in the broad context of armed conflict zones in developing countries, particularly in the IS domain. Second, extant literature emphasizes mHealth implementation, while neglecting the scale‐up and sustainability of these technologies. Therefore, this study employs activity theory as a holistic lens to explore how contradictions shape the scale‐up and sustainability of mHealth in the armed conflict zone of developing countries. In this study, rather than viewing contradiction as a challenge, it serves as a driver for effecting changes that can foster scale‐up and sustainability. The Algorithm for the Management of Acute Childhood Illnesses (ALMANACH), provides an empirical basis for this study. The research employs the interpretivism philosophy and the case study method. In‐depth interviews, participatory observations, and document reviews were used to collect data. Purposive and snowball sampling techniques were used to select the study's participants. The study reveals a lack of professional expertise among the CHWs, the non‐involvement of the users and beneficiaries in designing ALMANACH, and the lack of financial compensation for using ALMANACH in practice as contradictions. The study further exposes how community volunteer groups and the ALMANACH scientific board were established to steer demand. [ABSTRACT FROM AUTHOR]

Background: An increased risk of diabetes mellitus (DM) after COVID-19 has been reported in the United States, Europe, and Asia. The burden of COVID-related DM has yet to be described in Africa, where the overall risk of DM has been increasing rapidly. Our objective was to compare the prevalence of pre-DM and DM in Nigerian individuals with a history of COVID-19 to individuals without known COVID-19 infection. Methods: We undertook a retrospective cohort study with 256 individuals with a past medical history of COVID-19 with no history of pre-DM or DM and 256 individuals without a history of COVID-19 or pre-DM/DM. Participants were categorized as pre-DM (fasting capillary glucose 100–125 mg/dL) or DM (fasting capillary glucose ≥ 126 mg/dL). We employed univariate and multivariable logistic regression to identify key predictors and adjust for confounders related to hyperglycaemia risk factors. Additionally, we used multinomial logistic regression to analyze the relationship between COVID-19 history and diabetes status, distinguishing between normal, pre-diabetic, and diabetic glucose levels. All models were adjusted for age, gender, hypertension, physical activity, central adiposity, and family history of DM. Results: Compared to the control group, those with a history of COVID-19 had a similar median age (38 vs. 40 years, p = 0.84), had a higher proportion of men (63% vs. 49%), and had a lower prevalence of central adiposity (waist: hip ratio ≥ 0.90 for males and WHR ≥ 0.85 for females) (48% vs. 56.3%, p = 0.06). Of the 256 with a history of COVID-19, 44 (17%) required in-patient care. The median (interquartile range) time interval between COVID-19 diagnosis and the glycaemic assessment was 19 (IQR: 14, 24) months. Pre-DM prevalence was 27% in the post-COVID-19 group and 4% in the control group, whereas the prevalence of DM was 7% in the post-COVID-19 group and 2% in the control group. After multivariable adjustment, the odds of pre-DM were 8.12 (95% confidence interval (CI): 3.98, 16.58; p < 0.001) higher, and the odds of DM were 3.97 (95% CI: 1.16, 13.63) higher in those with a history of COVID-19 compared to controls. In the adjusted multinomial logistic regression analysis, individuals with a history of COVID-19 exhibited significantly elevated risks for pre-diabetes (RRR = 7.55, 95% CI: 3.76–15.17) and diabetes (RRR = 3.44, 95% CI: 1.01–11.71) compared to those without COVID-19. Conclusion: Previous COVID-19 was found to be a risk factor for prevalent pre-diabetes and diabetes mellitus in Nigeria. More intensive screening for DM in those with a history of COVID-19 should be considered. [ABSTRACT FROM AUTHOR]

There is a consensus in the information systems (IS) discipline that conflicting views among those implementing IS could result in critical implementation challenges. Prior studies on implementing smartphone‐based disease surveillance systems highlight the emergence of diverse perceptions of the system among stakeholder groups. It is argued that these various perceptions play a role in achieving the project's objectives, particularly when there is a strong incongruence. This study examines key stakeholders' interpretations of a smartphone‐based acute flaccid paralysis (AFP) surveillance system and how these interpretations have influenced the resulting outcomes. We adopt a qualitative interpretive case study method with theoretical underpinnings of technological frames (TF). The findings were drawn from observations, and semi‐structured interviews with project managers (PMs), community health workers (CHWs), informants (CHIs), and disease surveillance and notification officers (DSNOs) in Kano and Adamawa states northern Nigeria. Our findings reveal that training, implementation context, and technical infrastructure use socially shape the smartphone‐based AFP surveillance project. The results also illustrated how TF evolve. We present a model that explains the relationship between these factors and recommendations to manage conflicting views among stakeholder groups. [ABSTRACT FROM AUTHOR]

Sabore field is characterised by a high level of artisan activities that contributes to water pollution by heavy metals; these heavy metals when present in drinking water can be deleterious to human health. Consequently, in 2018 we investigated the seasonal variations of the water samples from the Sabore vicinity to determine its suitability for drinking. Six metals (Mn, Cu, Cd, Zn, Ni, Pb) were studied, the health risk assessment was investigated using Hazard Index (HI), Hazard Quotient (HQ) and Cancer Risk (CR). The results showed that water from this locality have HI values > 1, Pb and Cd were top contributors to non-carcinogenic risk while Ni and Cd caused concern for carcinogenic health risk making it unsuitable for consumption. The seasonal spread of the metals shows that Mn varied from 148 to 976 µg/L; Cu from 923 to 1676 µg/L; Cd from 1.167 to 22.5 µg/L; Zn from 63 to 118 µg/L, Ni from 37 to 95 µg/L and Pb from 128 to 185 µg/L in the rainy season. For the dry season, Mn shows a spread of 1442–1802 µg/L; 344–776 µg/L for Cu; 57–82 µg/L for Cd; 48–187 µg/L for Zn; 147–242 µg/L for Ni and 79–256 µg/L for Pb. The increased concentration of some metals during the dry seasons could be attributed to the increased human activities around the field, increased evaporation rate, absence of rainfall and runoff water. The heavy metal content of water from some of the sites exceeded the stipulated permissible limits and poses serious health risk to its consumers. [ABSTRACT FROM AUTHOR]

Healthcare workers (HCWs) face an unprecedented higher risk of COVID-19 infection due to their work and exposure. In this study, we aim to examine the associated risk factors for COVID-19 infection among HCWs in North-East Nigeria. We used data collected retrospectively among a cohort of clinical and non-clinical HCWs in six healthcare facilities in Adamawa State, Nigeria. We estimated the marginal probability of COVID-19 infection among HWCs using alternating logistic regression via the generalized estimating equations (GEE) approach. Among the 318 HCWs, 178 (55.97%) were males, mean (±SD) age was 36.81 (±8.98), 237 (74.76%) were clinical, and 80 (25.24) were non-clinical staff. The overall prevalence of COVID-19 was 16.67% among HCWs. After adjusting for other variables in the model, our results showed that clinical staff had a 5-fold higher risk of COVID-19 infection than non-clinical staff (aOR = 5.07, 95% CI: 1.32–19.52). Moreover, significant exposure risk factors for COVID-19 infection for HCWs increase with age, time spent attending to patients, caring for COVID-19 patients, and having worked with COVID-19 samples, while the risk decreases with the use of an N95 mask. Our findings suggested that the burden of COVID-19 infection is higher for clinical staff than non-clinical staff, and increasing age contributed to the increased risk. [ABSTRACT FROM AUTHOR]

Communities affected by armed conflict are striving to provide access to effective healthcare services in countries like Nigeria, where there exists a fragile healthcare system with an acute deficit of manpower and resources. This fragility has a negative impact on child health service delivery. mHealth is considered an excellent platform for enhancing/transforming the activities of community health workers (CHWs) in the delivery of effective health services. This paper aims to explore how mHealth implementation mediates and transforms the activities of CHWs in an armed conflict setting using activity theory as a lens. An interpretive research methodology was used, and the method of data collection was done mainly by participatory observations and interviews. The findings show that the introduction of an mHealth tool can transform the activities of CHWs in various ways. The study contributes to information systems research by broadening our understanding of the implementation of mHealth in armed conflict settings. [ABSTRACT FROM AUTHOR]