Factors associated with COVID-19 infections and mortality in Africa: A cross-sectional study using publicly available data

BMJ Open, Volume 10, No. 11, Year 2020

Interprétation

Introduction The current COVID-19 pandemic is a global threat. This elicits questions on the level of preparedness and capacity of health systems to respond to emergencies relative to other parts of the world. Methods This cross-sectional study uses publicly available core health data for 53 African countries to determine risk factors for cumulative COVID-19 deaths and cases per million in all countries in the continent. Descriptive statistics were determined for the indicators, and a negative binomial regression was used for modelling the risk factors. Results In sub-Saharan Africa, an increase in the number of nursing and midwifery personnel decreased the risk of COVID-19 deaths (p=0.0178), while a unit increase in universal healthcare (UHC) index of service coverage and prevalence of insufficient physical activity among adults increased the risk of COVID-19 deaths (p=0.0432 and p=0.0127). An increase in the proportion of infants initiating breast feeding reduced the number of cases per million (p<0.0001), while an increase in higher healthy life expectancy at birth increased the number of cases per million (p=0.0340). Conclusion Despite its limited resources, Africa's preparedness and response to the COVID-19 pandemic can be improved by identifying and addressing specific gaps in the funding of health services delivery. These gaps impact negatively on service delivery in Africa, which requires more nursing personnel and increased UHC coverage to mitigate the effects of COVID-19. This is a cross-sectional study of the most recent 2020 data for African countries extracted from the WHO Global Health Observatory Repository.7 Before extraction, the research team reviewed available indicators in the 2018 Global Reference List of 100 Core Health Indicators (plus health-related Sustainable Development Goals (SDGs))8 and listed different indicators by thematic areas. These indicators directly or indirectly describe the potential ability of a country’s health system to respond to the health needs of the population and may further determine the extent available services can be expanded to accommodate emergencies. Data on confirmed cases of coronavirus and deaths were obtained from the Worldometer Coronavirus Live Update.9 Bacille Calmette-Guérin (BCG) immunisation coverage among 1 year olds (%): BCG immunisation coverage among 1 year olds (%).10 Nursing and midwifery personnel (per 10 000 population): it is the density of nurses and midwifery personnel per 10 000 people.10 UHC index of service coverage: coverage of essential health services such as reproductive, maternal, newborn and child health among others.10 Prevalence of insufficient physical activity among adults aged 18+ years: insufficient physical activity was defined as adults not meeting the WHO recommendations on physical activity for health, that is, at least 150 min of moderate intensity or 75 min of vigorous intensity physical activity per week, or any equivalent combination of the two.11 Early initiation of breast feeding (%): initiation of breast feeding within the first hour of birth and exclusively breast fed for the first 6 months of life.12 Healthy life expectancy at birth (years): this is a life expectancy estimate that applies disability weights to health states to compute the equivalent number of years of good health that a new born can expect.13 Life expectancy at birth: this reflects the overall mortality level of a population. It summarises the mortality pattern that prevails across all age groups—children and adolescents, adults and the elderly.14 Prevalence of overweight among adults: adults with a body mass index ≥30. Current health expenditure (CHE) as a percentage of gross domestic product (GDP): this indicates the level of resources channelled to health relative to other uses.10 Data for 32 indicators (or variables) from 12 thematic areas were extracted from the 2018 Global Reference List of 100 Core Health Indicators (table 1). The 12 thematic areas are mortality by age and sex, mortality by cause, morbidity, nutrition, environmental risk factors, non-communicable diseases, immunisation, essential health services, utilisation and access, health workforce, health information and health financing. Summary of thematic areas of health indicators *Data not available. SDG, Sustainable Development Goals; TB, tuberculosis. Data were extracted in.xls format for each variable and imported into STATA V.15.0 software. For each variable, the most recent data for all countries included in the study were retained with the corresponding year and country name in.dta format. The different variables were merged using the country name as the unique identifier to obtain the final data set used for the analysis. The countries were further categorised into their assigned WHO region and World Bank income group except Somalia that had missing data. All data on health indicators were continuous and were analysed descriptively using median, IQR and minimum and maximum values. Of the 53 countries included in the analyses, there were varying proportions of <10% missing data. To address this, we assumed a missing at random mechanism and applied a multiple imputation technique with 10 imputations and summarised the results across all the datasets.15 The fit of the multiple imputation was evaluated using variance information measures including relative efficiency. The process of selection of variables for analysis was as follows. First, the team reviewed all the core publicly available health indicators. Then the plausibility of the explanatory power of these variables in the context of this study was subjected to various statistical approaches. These include the use of univariate and multivariate regression selection procedures. This approach enabled the identification of the final variables. Due to its flexibility in allowing for overdispersion, risk factors for cumulative COVID-19 deaths and cases per million were fitted using the negative binomial regression. Both univariate and multivariate regression models were fitted. In the multivariate model, a full model including all the variables was fitted and the final model determined using the backward selection procedure. Regression models were fitted for SSA followed by a sensitivity analyses including all the countries in the continent. Model fit was assessed using the ratio of the deviance, scaled deviance, Pearson χ2 and scaled Pearson χ2 divided by the df. Additionally, we also assessed model fit using the cumulative sum of residual plots with 10 000 replications. Deaths and cases per million were those reported in the Worldometer as of 29 May 2020. All statistical analyses were conducted using SAS Enterprise Guide V.7.15. This study used publicly available health indicators and aggregated COVID-19 cases and deaths. No patients were involved.

Résumé de l’IA

Study Justification:

– The study aims to assess the factors associated with COVID-19 infections and mortality in Africa.
– It addresses the level of preparedness and capacity of health systems in Africa to respond to the pandemic.
– The study uses publicly available data to provide insights into the risk factors for COVID-19 deaths and cases per million in African countries.

Study Highlights:

– Increase in nursing and midwifery personnel decreases the risk of COVID-19 deaths in sub-Saharan Africa.
– Universal healthcare (UHC) coverage and prevalence of insufficient physical activity among adults increase the risk of COVID-19 deaths.
– Increase in the proportion of infants initiating breastfeeding reduces the number of cases per million.
– Higher healthy life expectancy at birth increases the number of cases per million.

Study Recommendations:

– Improve funding for health services delivery in Africa to enhance preparedness and response to the COVID-19 pandemic.
– Increase the number of nursing personnel to mitigate the effects of COVID-19.
– Expand universal healthcare coverage to ensure access to essential health services.
– Promote initiatives to encourage physical activity among adults.
– Support and promote early initiation of breastfeeding.

Key Role Players:

– Ministry of Health officials
– Public health experts and researchers
– Healthcare providers and professionals
– Non-governmental organizations (NGOs) working in healthcare
– International organizations and donors

Cost Items for Planning Recommendations:

– Funding for health services delivery
– Recruitment and training of nursing personnel
– Infrastructure and equipment for healthcare facilities
– Awareness campaigns and initiatives promoting physical activity
– Support for breastfeeding programs and education
Please note that the cost items provided are general categories and not actual cost estimates. The actual cost will depend on various factors such as the specific context and resources available in each country.

Force de la preuve

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is a cross-sectional study, which provides valuable insights into risk factors for COVID-19 infections and mortality in Africa. The study uses publicly available data from reputable sources such as the WHO and Worldometer. The statistical analysis includes both univariate and multivariate regression models, which adds to the robustness of the findings. However, there are a few limitations that could be addressed to improve the strength of the evidence. First, the study relies on aggregated COVID-19 cases and deaths, which may not capture the full picture of the pandemic in Africa. Second, the study does not provide information on the sample size or representativeness of the countries included in the analysis. Third, the study does not discuss potential confounding factors that could influence the observed associations. To improve the evidence, future studies could consider using individual-level data, ensuring a representative sample, and addressing potential confounding factors in the analysis.

Abstrait

This is a cross-sectional study of the most recent 2020 data for African countries extracted from the WHO Global Health Observatory Repository.7 Before extraction, the research team reviewed available indicators in the 2018 Global Reference List of 100 Core Health Indicators (plus health-related Sustainable Development Goals (SDGs))8 and listed different indicators by thematic areas. These indicators directly or indirectly describe the potential ability of a country’s health system to respond to the health needs of the population and may further determine the extent available services can be expanded to accommodate emergencies. Data on confirmed cases of coronavirus and deaths were obtained from the Worldometer Coronavirus Live Update.9 Bacille Calmette-Guérin (BCG) immunisation coverage among 1 year olds (%): BCG immunisation coverage among 1 year olds (%).10 Nursing and midwifery personnel (per 10 000 population): it is the density of nurses and midwifery personnel per 10 000 people.10 UHC index of service coverage: coverage of essential health services such as reproductive, maternal, newborn and child health among others.10 Prevalence of insufficient physical activity among adults aged 18+ years: insufficient physical activity was defined as adults not meeting the WHO recommendations on physical activity for health, that is, at least 150 min of moderate intensity or 75 min of vigorous intensity physical activity per week, or any equivalent combination of the two.11 Early initiation of breast feeding (%): initiation of breast feeding within the first hour of birth and exclusively breast fed for the first 6 months of life.12 Healthy life expectancy at birth (years): this is a life expectancy estimate that applies disability weights to health states to compute the equivalent number of years of good health that a new born can expect.13 Life expectancy at birth: this reflects the overall mortality level of a population. It summarises the mortality pattern that prevails across all age groups—children and adolescents, adults and the elderly.14 Prevalence of overweight among adults: adults with a body mass index ≥30. Current health expenditure (CHE) as a percentage of gross domestic product (GDP): this indicates the level of resources channelled to health relative to other uses.10 Data for 32 indicators (or variables) from 12 thematic areas were extracted from the 2018 Global Reference List of 100 Core Health Indicators (table 1). The 12 thematic areas are mortality by age and sex, mortality by cause, morbidity, nutrition, environmental risk factors, non-communicable diseases, immunisation, essential health services, utilisation and access, health workforce, health information and health financing. Summary of thematic areas of health indicators *Data not available. SDG, Sustainable Development Goals; TB, tuberculosis. Data were extracted in.xls format for each variable and imported into STATA V.15.0 software. For each variable, the most recent data for all countries included in the study were retained with the corresponding year and country name in.dta format. The different variables were merged using the country name as the unique identifier to obtain the final data set used for the analysis. The countries were further categorised into their assigned WHO region and World Bank income group except Somalia that had missing data. All data on health indicators were continuous and were analysed descriptively using median, IQR and minimum and maximum values. Of the 53 countries included in the analyses, there were varying proportions of <10% missing data. To address this, we assumed a missing at random mechanism and applied a multiple imputation technique with 10 imputations and summarised the results across all the datasets.15 The fit of the multiple imputation was evaluated using variance information measures including relative efficiency. The process of selection of variables for analysis was as follows. First, the team reviewed all the core publicly available health indicators. Then the plausibility of the explanatory power of these variables in the context of this study was subjected to various statistical approaches. These include the use of univariate and multivariate regression selection procedures. This approach enabled the identification of the final variables. Due to its flexibility in allowing for overdispersion, risk factors for cumulative COVID-19 deaths and cases per million were fitted using the negative binomial regression. Both univariate and multivariate regression models were fitted. In the multivariate model, a full model including all the variables was fitted and the final model determined using the backward selection procedure. Regression models were fitted for SSA followed by a sensitivity analyses including all the countries in the continent. Model fit was assessed using the ratio of the deviance, scaled deviance, Pearson χ2 and scaled Pearson χ2 divided by the df. Additionally, we also assessed model fit using the cumulative sum of residual plots with 10 000 replications. Deaths and cases per million were those reported in the Worldometer as of 29 May 2020. All statistical analyses were conducted using SAS Enterprise Guide V.7.15. This study used publicly available health indicators and aggregated COVID-19 cases and deaths. No patients were involved.

Matériaux

Innovations

Based on the provided description, it seems that the study focuses on identifying risk factors for COVID-19 infections and mortality in African countries. While the description does not explicitly mention innovations to improve access to maternal health, there are potential recommendations that can be derived from the findings of the study. These recommendations could be considered as innovations to improve access to maternal health in the context of the COVID-19 pandemic in Africa. However, it’s important to note that these recommendations are speculative and should be further explored and validated through additional research and expert consultation.

1. Increase the number of nursing and midwifery personnel: The study found that an increase in the number of nursing and midwifery personnel decreased the risk of COVID-19 deaths. This suggests that investing in and expanding the healthcare workforce, particularly in the field of maternal health, could improve access to quality care for pregnant women.

2. Enhance universal healthcare (UHC) coverage: The study found that an increase in the UHC index of service coverage increased the risk of COVID-19 deaths. However, improving UHC coverage in terms of essential health services, including reproductive, maternal, newborn, and child health, could contribute to better access to maternal healthcare during the pandemic.

3. Promote early initiation of breastfeeding: The study found that an increase in the proportion of infants initiating breastfeeding reduced the number of COVID-19 cases per million. Encouraging and supporting early initiation of breastfeeding can have multiple benefits for both the mother and the newborn, including improved immune protection and reduced risk of infections.

4. Address the prevalence of insufficient physical activity among adults: The study found that a higher prevalence of insufficient physical activity among adults increased the risk of COVID-19 deaths. Promoting physical activity among pregnant women and providing appropriate guidance and resources for safe exercise during pregnancy can contribute to better maternal health outcomes.

5. Improve funding for health services delivery: The study suggests that addressing specific gaps in the funding of health services delivery can improve Africa’s preparedness and response to the COVID-19 pandemic. Allocating adequate resources to maternal health programs and services can help ensure access to essential care for pregnant women, especially during emergencies.

It’s important to note that these recommendations are based on the findings of the study and may need to be further explored and adapted to the specific context and needs of each African country. Additionally, other innovations and interventions may also be necessary to comprehensively improve access to maternal health during the COVID-19 pandemic.

AI Innovations Description

Based on the information provided, the study identifies several factors associated with COVID-19 infections and mortality in Africa. The study suggests that improving access to maternal health can help mitigate the effects of COVID-19. Here is a recommendation that can be developed into an innovation to improve access to maternal health:

1. Telemedicine and Mobile Health: Develop and implement telemedicine and mobile health solutions to provide remote access to maternal health services. This can include virtual consultations, remote monitoring of maternal health indicators, and access to educational resources for pregnant women.

2. Community Health Workers: Train and deploy community health workers to provide maternal health services in remote or underserved areas. These workers can provide prenatal care, assist with deliveries, and offer postnatal support to ensure the well-being of both mothers and infants.

3. Mobile Clinics: Establish mobile clinics that can travel to rural or hard-to-reach areas to provide maternal health services. These clinics can offer prenatal check-ups, vaccinations, and health education to pregnant women who may not have easy access to healthcare facilities.

4. Maternal Health Vouchers: Introduce a voucher system that provides financial assistance to pregnant women, enabling them to access essential maternal health services. These vouchers can cover prenatal care, delivery services, and postnatal care, ensuring that cost is not a barrier to accessing quality care.

5. Strengthening Health Systems: Invest in strengthening healthcare infrastructure and systems to ensure that maternal health services are readily available and of high quality. This can include training healthcare professionals, improving facilities, and ensuring the availability of essential medical supplies and equipment.

By implementing these recommendations, access to maternal health can be improved, leading to better outcomes for both mothers and infants, and ultimately contributing to the overall improvement of healthcare in Africa.

AI Innovations Methodology

Based on the provided information, it seems that the request is to consider innovations that can improve access to maternal health and describe a methodology to simulate the impact of these recommendations. However, the given text is a description of a cross-sectional study on COVID-19 infections and mortality in Africa, and it does not directly address innovations for improving access to maternal health.

To provide relevant information, here are some potential innovations that can improve access to maternal health:

1. Telemedicine and mobile health (mHealth) solutions: These technologies can provide remote access to healthcare services, allowing pregnant women to consult with healthcare providers, receive prenatal care, and access health information through their mobile devices.

2. Community-based interventions: Implementing community health workers or midwives who can provide prenatal care, education, and support to pregnant women in their communities. This can help overcome geographical barriers and improve access to maternal health services.

3. Maternal health clinics or mobile clinics: Establishing dedicated clinics or mobile units that specifically focus on providing maternal health services, including prenatal care, delivery, and postnatal care. These clinics can be strategically located in underserved areas to improve access.

4. Financial incentives and subsidies: Providing financial incentives or subsidies to pregnant women, especially those from low-income backgrounds, to encourage them to seek and receive timely maternal health services.

5. Health information systems: Implementing robust health information systems that can track and monitor maternal health indicators, identify gaps in service delivery, and facilitate data-driven decision-making to improve access and quality of care.

Now, regarding the methodology to simulate the impact of these recommendations on improving access to maternal health, here is a general approach:

1. Define the objectives: Clearly define the specific outcomes or indicators that you want to measure or improve, such as the number of pregnant women receiving prenatal care or the reduction in maternal mortality rates.

2. Collect baseline data: Gather relevant data on the current state of maternal health access in the target population or region. This can include information on the number of healthcare facilities, healthcare providers, utilization rates, and health outcomes.

3. Develop a simulation model: Create a simulation model that incorporates the identified innovations and their potential impact on improving access to maternal health. This model should consider factors such as population demographics, geographical distribution, healthcare infrastructure, and resource availability.

4. Input data and parameters: Input the collected baseline data and relevant parameters into the simulation model. This can include data on the target population, healthcare resources, utilization rates, and the expected impact of the innovations.

5. Run simulations: Run multiple simulations using different scenarios and assumptions to assess the potential impact of the innovations on improving access to maternal health. This can involve varying factors such as the scale of implementation, coverage, and effectiveness of the innovations.

6. Analyze results: Analyze the simulation results to evaluate the potential impact of the innovations on the desired outcomes. This can include assessing changes in access indicators, health outcomes, and cost-effectiveness.

7. Refine and validate the model: Continuously refine and validate the simulation model based on feedback, additional data, and real-world observations. This will help improve the accuracy and reliability of the simulations.

8. Implement and monitor: Based on the simulation results, implement the recommended innovations and closely monitor their actual impact on improving access to maternal health. Continuously evaluate and adjust the interventions based on real-world data and feedback.

It is important to note that the specific methodology and tools used for simulation may vary depending on the context and available resources. Consulting with experts in the field and utilizing appropriate statistical and modeling techniques can further enhance the accuracy and reliability of the simulations.

Auteurs et co-auteurs

Statistics:

Citations: 15

Authors: 3

Identifiers:

DOI: 10.1136/bmjopen-2020-042750

Research Areas:

COVID, Disability, Food Security, Health System and Policy, Infectious Diseases, Maternal and Child Health, Noncommunicable Diseases, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Somalia

Study Design:

Cross Sectional Study

Study Approach:

Quantitative

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