Covid-19 Infection, Illness and Deaths Among Healthcare Workers in Low- and Middle-income Countries: A Systematic Review Protocol

Background: Globally, health care workers continue to be infected, fall ill and die at the frontline of the Coronavirus Disease 2019 (COVID-19) ght, an indicator of inadequate safety in health facilities. This rapid evidence synthesis aims to highlight the impacts of COVID-19 on healthcare workers in low-and middle-income countries (LMICs) in terms of infections, illnesses and deaths. Methods: A systematic review will be done. Article search will be performed by an experienced librarian in PubMed, MEDLINE Ovid, Google Scholar, COVID-END, Cochrane library and targeted search from other relevant sources. MeSH terms and Boolean operators “AND” and “OR” will be used in the article search. Independent reviewers will screen the retrieved articles using a priori criteria. Data abstraction will be done using an excel based abstraction tool and synthesized using structured narratives and summary of ndings tables. Discussion: This evidence synthesis seeks to analyze the impact of COVID-19 on the healthcare systems of low- and middle-income countries. Information on healthcare worker infections, illness, and deaths due to COVID-19, will be collated from published research articles. This will help guide decision makers in establishing low- cost high impact interventions to mitigate the effects of COVID-19 in the health work force.

Independent reviewers will screen the retrieved articles using a priori criteria. Data abstraction will be done using an excel based abstraction tool and synthesized using structured narratives and summary of ndings tables.
Discussion: This evidence synthesis seeks to analyze the impact of COVID-19 on the healthcare systems of low-and middle-income countries. Information on healthcare worker infections, illness, and deaths due to COVID-19, will be collated from published research articles. This will help guide decision makers in establishing low-cost high impact interventions to mitigate the effects of COVID-19 in the health work force.
Protocol registration: PROSPERO CRD 42020204174 [1] [1] This protocol registration can be found at; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020204174 Background Coronavirus disease (COVID-19) has caused unprecedented morbidity and mortality across the globe since its outbreak in December 2019. The WHO has reported over 80 million infections and about 1.8 million deaths by 30th December 2020 (1). Consequently, the volume of patients and the resulting shortage of medical supplies have overwhelmed healthcare systems across the globe. The toll on healthcare professionals has thus been high.
Notably, healthcare workers are in close contact with patients of known and unknown COVID-19 disease status (2). Their nature of work puts them at a higher risk of contracting contagious diseases and thus necessitates a need for personal protective equipment (PPEs) and safe working environment. Unfortunately, PPEs are often inadequate in low-and middle-income countries (LMICs). Ironically, this has been the case even in high-income countries (3), however LMICs are likely to be more affected due to inadequate healthcare systems.
Healthcare workers often have to endure working within limited health infrastructure setting that increases the risk of contracting COVID-19. There's a need to equip policy makers and implementers with evidence to guide in establishing decent and safe healthcare working environments especially in LMICs.
Our preliminary search indicates that indeed, a number of healthcare workers worldwide have been infected and worse still died of COVID-19. Despite speculations from several sources about the extent of COVID-19 infections, illnesses and deaths among health workers, there is a dearth of context speci c information in LMICs, especially sub-Saharan Africa.
COVID-19 has placed an unprecedented pressure on the already overwhelmed healthcare systems of LMICs. It is against this background that we intend to collate evidence from published research, to provide resource tools and guide policymakers in decision-making for appropriate interventions. The evidence synthesis aims to highlight the impact of COVID-19 on healthcare workers in LMICs in terms of infections, illnesses and deaths; and to drive the agenda of healthcare worker safety to policy windows. Speci cally, we intend to determine the prevalence of COVID-19 infections, illnesses and the COVID-19 case fatality rate among health workers in LMICs.

Methods
The protocol for this evidence synthesis has been registered with the International Prospective Register of Systematic Reviews (PROSPERO; Registration number: CRD42020204174). The protocol was developed following PRISMA-P+ (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) checklist (4) -additional le 2.

Review question
The review will follow the PECOS model. Population are the healthcare workers; Exposure is working in LMIC healthcare settings during the COVID-19 pandemic; Comparator, no comparator; Outcome is COVID-19 infection, illness and deaths as primary outcomes and COVID-19 co-morbidities like mental health outcomes, plus other associated factors such as underlying medical conditions and adverse effects to interventions shall be secondary outcomes; Study designs that will be considered include cross-sectional, case-control, cohort studies and randomized controlled trials, as well as Systematic Reviews and Metaanalyses. The period covered will be from December 2019 to date.

Systematic review objectives
The rst objective of this review is to determine the prevalence of COVID19 infections and illnesses among healthcare workers in low-and middle-income countries. Secondly, we seek to estimate the COVID-19 case fatality rate among healthcare workers in low-and middle-income countries.

Inclusion criteria
Eligible studies should report ndings on infection, illness and/or death due to COVID-19. Studies will be limited to those conducted among adult healthcare workers, above the age of 18 years, working in healthcare settings in LMICs during the COVID-19 pandemic. The review will also include studies conducted among the general population with healthcare workers as a sub group if results are strati ed. Primary observational studies with cross sectional or prospective research designs, case control studies, systematic reviews, and meta-analyses and studies with experimental designs shall be included. Only studies published after December 2019 will be included in the review.

Exclusion criteria
Case reports and series of single case studies, programme reports, conference abstracts, author's opinions and editorials shall not be included in this review. Studies not published in the English language shall be excluded.

Information sources
Data sources for the review will include PubMed (preliminary search done on June 30th, 2020), MEDLINE Wuhan pneumonia. Terms for healthcare workers were tested in the pilot Health worker*, healthcare worker*, health professional*, healthcare professional*, nurses, doctors, ambulance driver*, physician*, laboratory technician*, and the LMIC lter by Cochrane was used to lter articles in all Low-and middleincome countries.

Search strategy
An experienced information scientist (AAK) will conduct article search. Medical Subject Headings (MeSH) will be used in article search. The unique terms will be combined using Boolean operators "OR", "AND" or "NOT". Targeted search for additional relevant articles for this review will be done manually from references of included articles, and grey literature will be considered. The pilot PubMed search string is attached as an additional le 3.

Article screening
All the articles identi ed from the search will be exported into Endnote and duplicates removed. Article screening will be done using a priori criteria. BAK, RNN and RNW will independently screen articles following the PRISMA ow. Any disagreements between the reviewers will be resolved through consensus. A tie breaker will resolve further disagreements (OM, EAO).

Data abstraction and management
A data abstraction tool will be developed in Excel spreadsheet 2007 (Microsoft Corporation, WA, USA, www.microsoft.com). This tool will capture administrative information as author, title, citation, country, ethical approval, funding, year of publication; methodological data such as study design, sample size, COVID-19 test con rmation method, profession, type of healthcare setting; and outcomes such as number infected, mortality, duration of illness, nature of care for example, need for Intensive Care Unit (ICU) or not, prevalence and case fatality. Ascertainment of infection as an outcome of interest will be through WHO approved laboratory tests for COVID-19, whereas ascertainment of illness or death will be through verbal autopsy or clinical assessment reports. Three reviewers BAK, RNW and RNN will do abstraction.

Data synthesis and analysis
Abstracted data from the included articles will be exported to an open access review management software or EPPI-Reviewer (Evidence for Policy and Practice Information) for analysis. Results from the analysis will be presented as structured narratives or summaries in data tables and graphs where applicable measures of central tendencies (means and frequencies) which will be used for descriptive statistics. Random effects model, which assumes a hierarchical linear model will be used in metaanalysis, if appropriate.

Heterogeneity analysis
The level of heterogeneity will be assessed using the Higgins I 2 statistic. It will be used to indicate percentage (%) heterogeneity that can be attributed to between-study variance. Interpretation: I 2 = 25% (low heterogeneity), I 2 = 50% (moderate heterogeneity), I 2 = 75% (high heterogeneity). Sub-group analysis will be done for articles with low and moderate heterogeneity.

Publication bias
Publication bias will be examined using a funnel plot while using the asymmetry of the plots to detect likelihood of publication bias among included articles (1).

Risk of bias assessment
This evidence synthesis shall undertake critical quality control assessment at every stage of the review. Biases such as selection bias, outcome assessment bias, attrition bias and analysis bias are expected within the included primary studies. Quality assessment will be done using the New Castle Ottawa tools for Case-control as well as for Observational Cohort and Cross-Sectional Studies to critically appraise the selected studies (5). The AMSTAR-2 (A MeaSurement Tool to Assess Systematic Reviews 2) Systematic Review Critical Appraisal Tool (6) shall be used to assess quality of the included systematic reviews. The overall quality of the body of evidence will be graded using the GRADE (Grading of Recommendations, Assessment, Development and Evaluations) framework (8). The immediate output will be a rapid evidence brief for policy in line with the SURE Guidelines (Supporting the Use of Research Evidence), which will inform a results deliberation/policy dialogue (9).

Discussion
Most healthcare systems in LMICs are inadequately funded and are unable to meet the healthcare needs of the entire population. For instance, despite the 2001 Abuja declaration by African Union states, which stated that 15% budget allocation should be directed towards the health sector, only 6 countries out of 54 hit the mark 10 years down the road. On the contrary, some countries cut their health budgets instead (10). In the wake of a global pandemic like the COVID-19 disease, a poorly funded healthcare sector is likely to be disproportionately affected. This has put healthcare workers in such settings at a higher risk of COVID-19 infection compared to the general population.
The nature of work of health workers puts them at risk of occupational biohazards including nosocomial infections like Coronavirus. There has been an in ux of patients to treatment centres, constraining the global health systems which are already complicated by de cits in medical supplies (11). As a result, the healthcare workforce is under great physiological and psychological pressure (2). Emerging evidence from recent studies not only suggests that the health professionals' nature of work puts them at increased risk of acquiring COVID-19, but also other stressful work challenges. The challenges range from medical staff physical and mental exhaustion, the torment of di cult triage decisions, stress and the pain of losing a patient and colleagues (12). Consequently, more than 90, 000 health workers globally are estimated to have been infected with COVID-19 and over 1500 reported dead (13).
Whereas these effects are clearly known, there is a lack of conformity on the magnitude of risk the disease poses on the health workers. One study has reported 8.4% prevalence of COVID-19 infections among health workers in Italy (14). A more extensive study giving a two months' picture of COVID-19 in the United States of America showed that a quarter of the infections were among health workers. This study also indicated that most of the infected health workers did not require hospitalisation while less than 5% were admitted into the ICU (15). Furthermore, there is evidence showing higher rates of infections in this group of professionals (16). This review will focus on generating an up-to-date picture of the outcomes of COVID 19 (including infections, illnesses and deaths) among health workers in LMICs.
Understanding the burden of COVID-19 among healthcare workers in LMICs provides an avenue for redesigning healthcare systems to not only provide appropriate care to the population, but also to protect the healthcare workers at the forefront of containing the pandemic right from the policy level to the healthcare facility level. Liyanage & Egbu present a conceptual framework for the control of Healthcare Associated Infections (HAI) in Facility Management (FM) services (17). FM includes; (i) availability of infection control facilities, (ii) utilization of these facilities, and (iii) suitability of the facilities. However, it should be notable that most LMIC facilities lack basic infection control facilities and management like hand washing facilities, safe waste disposal, routine and regular cleaning of environment and adequate provision and knowledge of PPEs. As such, this review seeks to evaluate available evidence on COVID-19 among health workers in LMICs.
The ndings from this systematic review will help stakeholders in LMICs to appreciate the effect COVID-19 has had on healthcare workers and eventually on the healthcare systems. This will guide decisionmakers in designing policies and programs that strengthen healthcare systems to satisfactorily manage pandemics while protecting the healthcare workers. 1. Healthcare worker: Throughout the systematic review, we will use the term "healthcare worker" to mean any adult who is employed to work and those training in a health care setting. Healthcare