Understanding the burden of SARS-CoV-2 infections among healthcare workers is a critical component to inform occupational health policy and strategy. We conducted a systematic review and meta-analysis to map and analayse the available global evidence on the prevalence of SARS-CoV-2 infections among healthcare workers. The random-effects adjusted pooled prevalence of COVID-19 among those studies that conducted the test using the antibody (Ab) method was 7% [95% CI: 3 to 17%]. The random-effects adjusted pooled prevalence of COVID-19 among those studies that conducted the test using the PCR method was 11% [95% CI: 7 to 16%]. We found the burden of COVID-19 among healthcare workers to be quite significant and therefore a cause for global health concern. Furthermore, COVID-19 infections among healthcare workers affect service delivery through workers’ sick leave, the isolation of confirmed cases and quarantine of contacts, all of which place significant strain on an already shrunken health workforce.

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Background Evidence on the spectrum of risk factors for infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among front-line healthcare workers (HCWs) has not been well-described. While several studies evaluating the risk factors associated with SARS-CoV-2 infection among patient-facing and non-patient-facing front-line HCWs have been reported since the outbreak of the coronavirus disease in 2019 (COVID-19), and several more are still underway. There is, therefore, an immediate need for an ongoing, rigorous systematic review that continuously assesses the risk factors of SARS-CoV-2 infection among front-line HCWs. Objective Here, we outline a protocol to serve as a guideline for conducting a living systematic review and meta-analysis to examine the burden of COVID-19 on front-line HCWs and identify risk factors for SARS-CoV-2 infection in patient-facing and non-patient-facing front-line HCWs. Methods The protocol was developed and reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). The conduct of the proposed living systematic review and meta-analysis will primarily follow the principles recommended in the Centre for Reviews and Dissemination (CRD) guidance for undertaking systematic reviews in healthcare, and the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines. The systematic literature searches will be performed using the EBSCOhost platform by searching the following databases within the platform: Academic search complete, health source: nursing/academic edition, CINAHL with full text, Embase, PubMed, MEDLINE, Science Direct databases, Google Scholar, and; also a search in the China National Knowledge Infrastructure and the World Health Organization library databases for relevant studies will be performed. The searches will include peer-reviewed articles, published in English and Mandarin language irrespective of publication year, evaluating the risk for testing positive for C0VID-19, the risk of developing symptoms associated with SARS-CoV-2 infection, or both, among front-line HCWs. The initial review period will consider articles published since the onset of COVID-19 disease to the present and then updated monthly. Review Manager (RevMan 5.3) will be used to pool the odds ratios or mean differences for individual risk factors where possible. Results will be presented as relative risks and 95% confidence intervals for dichotomous outcomes and mean differences, or standardised mean differences along with 95% confidence intervals, for continuous outcomes. The Newcastle–Ottawa Scale will be used to rate study quality, and the certainty of the evidence will be assessed by using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE). The results of the living systematic review and meta-analysis will be reported per the PRISMA guidelines. Discussion Though addressing the needs of front-line HCWs during the COVID-19 pandemic is a high priority, data to inform such initiatives are inadequate, particularly data on the risk factor disparities between patient-facing and non-patient-facing front-line HCWs. The proposed living systematic review and meta-analysis anticipate finding relevant studies reporting risk factors driving the SARS-CoV-2 infection rates among patient-facing and non-patient-facing front-line HCWs, thus providing subsidies for public health interventions and occupational health policies. The study results will be disseminated electronically, in print and through conference presentation, and key stakeholder meetings in the form of policy briefs. Trail registration PROSPERO registration number: CRD42020193508 available for public comments via the link below https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020193508).

In previous studies, food insecurity has been hypothesised to promote the prevalence of metabolic risk factors on the causal pathway to diet-sensitive non-communicable diseases (NCDs). This systematic review and meta-analysis aimed to determine the associations between food insecurity and key metabolic risk factors on the causal pathway to diet-sensitive NCDs and estimate the prevalence of key metabolic risk factors among the food-insecure patients in sub-Saharan Africa. This study was guided by the Centre for Reviews and Dissemination (CRD) guidelines for undertaking systematic reviews in healthcare. The following databases were searched for relevant literature: PubMed, EBSCOhost (CINAHL with full text, Health Source - Nursing, MedLine). Epidemiological studies published between January 2015 and June 2019, assessing the associations between food insecurity and metabolic risk outcomes in sub-Saharan African populations, were selected for inclusion. Meta-analysis was performed with DerSimonian-Laird’s random-effect model at 95% confidence intervals (CIs). The I2 statistics reported the degree of heterogeneity between studies. Publication bias was assessed by visual inspection of the funnel plots for asymmetry, and sensitivity analyses were performed to assess the meta-analysis results’ stability. The Mixed Methods Appraisal Tool (MMAT) – Version 2018 was used to appraise included studies critically. The initial searches yielded 11,803 articles, 22 cross-sectional studies were eligible for inclusion, presenting data from 26,609 (46.8% males) food-insecure participants, with 11,545 (42.1% males) reported prevalence of metabolic risk factors. Of the 22 included studies, we identified strong evidence of an adverse association between food insecurity and key metabolic risk factors for diet-sensitive NCDs, based on 20 studies. The meta-analysis showed a significantly high pooled prevalence estimate of key metabolic risk factors among food-insecure participants at 41.8% (95% CI: 33.2% to 50.8%, I2 = 99.5% p-value < 0.00) derived from 14 studies. The most prevalent type of metabolic risk factors was dyslipidaemia 27.6% (95% CI: 6.5% to 54.9%), hypertension 24.7% (95% CI: 15.6% to 35.1%), and overweight 15.8% (95% CI: 10.6% to 21.7%). Notably, the prevalence estimates of these metabolic risk factors were considerably more frequent in females than males. In this systematic review and meta-analysis, exposure to food insecurity was adversely associated with a wide spectrum of key metabolic risk factors, such as obesity, dyslipidaemia, hypertension, underweight, and overweight. These findings highlight the need to address food insecurity as an integral part of diet-sensitive NCDs prevention programmes. Further, these findings should guide recommendations on the initiation of food insecurity status screening and treatment in clinical settings as a basic, cost-effective tool in the practice of preventive medicine in sub-Saharan Africa.PROSPERO registration number: PROSPERO 2019 CRD42019136638.

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Background: Point of care (POC) testing has enabled rapid coronavirus disease 2019 (COVID-19) diagnosis in resource-limited settings with limited laboratory infrastructure and high disease burden. However, the accessibility of the tests is not optimal in these settings. This scoping review mapped evidence on supply chain management (SCM) systems for POC diagnostic services to reveal evidence that can help guide future research and inform the improved implementation of SARS-CoV-2 POC diagnostics in resource-limited settings. Methodology: This scoping review was guided by an adapted version of the Arksey and O’Malley methodological framework. We searched the following electronic databases: Medline Ovid, Medline EBSCO, Scopus, PubMed, PsychInfo, Web of Science and EBSCOHost. We also searched grey literature in the form of dissertations/theses, conference proceedings, websites of international organisations such as the World Health Organisation and government reports. A search summary table was used to test the efficacy of the search strategy. The quality of the included studies was appraised using the mixed method appraisal tool (MMAT) version 2018. Results: We retrieved 1206 articles (databases n = 1192, grey literature n = 14). Of these, 31 articles were included following abstract and full-text screening. Fifteen were primary studies conducted in LMICs, and 16 were reviews. The following themes emerged from the included articles: availability and accessibility of POC diagnostic services; reasons for stockouts of POC diagnostic tests (procurement, storage, distribution, inventory management and quality assurance) and human resources capacity in POC diagnostic services. Of the 31 eligible articles, 15 underwent methodological quality appraisal with scores between 90% and 100%. Conclusions: Our findings revealed limited published research on SCM systems for POC diagnostic services globally. We recommend primary studies aimed at investigating the barriers and enablers of SCM systems for POC diagnostic services for highly infectious pathogens such SARS-CoV-2 in high disease-burdened settings with limited laboratory infrastructures.

Mobile health devices are emerging applications that could help deliver point-of-care (POC) diagnosis, particularly in settings with limited laboratory infrastructure, such as Sub-Saharan Africa (SSA). The advent of Severe acute respiratory syndrome coronavirus 2 has resulted in an increased deployment and use of mHealth-linked POC diagnostics in SSA. We performed a systematic review and meta-analysis to evaluate the accuracy of mobile-linked point-of-care diagnostics in SSA. Our systematic review and meta-analysis were guided by the Preferred Reporting Items requirements for Systematic Reviews and Meta-Analysis. We exhaustively searched PubMed, Science Direct, Google Scholar, MEDLINE, and CINAHL with full text via EBSCOhost databases, from mHealth inception to March 2021. The statistical analyses were conducted using OpenMeta-Analyst software. All 11 included studies were considered for the meta-analysis. The included studies focused on malaria infections, Schistosoma haematobium, Schistosoma mansoni, soil-transmitted helminths, and Trichuris trichiura. The pooled summary of sensitivity and specificity estimates were moderate compared to those of the reference representing the gold standard. The overall pooled estimates of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of mobile-linked POC diagnostic devices were as follows: 0.499 (95% CI: 0.458–0.541), 0.535 (95% CI: 0.401–0.663), 0.952 (95% CI: 0.60–1.324), 1.381 (95% CI: 0.391–4.879), and 0.944 (95% CI: 0.579–1.538), respectively. Evidence shows that the diagnostic accuracy of mobile-linked POC diagnostics in detecting infections in SSA is presently moderate. Future research is recommended to evaluate mHealth devices’ diagnostic potential using devices with excellent sensitivities and specificities for diagnosing diseases in this setting.

BackgroundIn previous studies, food insecurity has been hypothesised to promote the prevalence of metabolic risk factors on the causal pathway to diet-sensitive non-communicable diseases (NCDs). This prevalence has been shown to differ between gender and populations. However, evidence of this association in resources-limited settings with high levels of food insecurity such as sub-Saharan African countries remains elusive. PurposeWe aimed to identify the association between food insecurity and key metabolic risk factors on the causal pathway to diet-sensitive NCDs in sub-Saharan African population. MethodsWe did a systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Relevant studies published between January 2015 and October 2019 were searched in PubMed, Web of Science (SCiELO Citation Index), and five other databases followed by explicit and reproducible hand-searches of included studies which were peer-reviewed epidemiological studies conducted in sub-Saharan Africa, directly measured food insecurity, and compared food insecurity to a metabolic risk factor outcome. Two reviewers extracted all the necessary data from individual studies independently and employed the Mixed Methods Appraisal Tool (MMAT) -Version 2018 to evaluate the risk of bias. Prevalence estimates from individual studies were pooled using the random-effect model. ResultsThe initial searches yielded 11 803 articles, 22 were eligible for inclusion, presenting data from 26 609 food-insecure participants and 11 545 incident of metabolic risk factor cases. Most studies confirmed an adverse association between food insecurity and key metabolic risk factors for dietsensitive NCDs. The Meta-analysis showed a significantly high pooled prevalence estimate of key metabolic risk factors at 41.8 per cent (95% CI: 33.2% to 50.8%, I 2 = 99.5% p-value < 0.00). The most prevalent type of metabolic risk factors was dyslipidaemia 27.6 per cent (95% CI: 6.5% to