One hundred thirty-three observed COVID-19 deaths in 10 months: unpacking lower than predicted mortality in Rwanda

Spatio-temporal dynamic of the COVID-19 epidemic and the impact of imported cases in Rwanda

INTRODUCTION

Africa was threatened by the coronavirus disease 2019 (COVID-19) due to the limited health care infrastructure. Rwanda has consistently used non-pharmaceutical strategies, such as lockdown, curfew, and enforcement of prevention measures to control the spread of COVID-19. Despite the mitigation measures taken, the country has faced a series of outbreaks in 2020 and 2021. In this paper, we investigate the nature of epidemic phenomena in Rwanda and the impact of imported cases on the spread of COVID-19 using endemic-epidemic spatio-temporal models. Our study provides a framework for understanding the dynamics of the epidemic in Rwanda and monitoring its phenomena to inform public health decision-makers for timely and targeted interventions.

RESULTS

The findings provide insights into the effects of lockdown and imported infections in Rwanda's COVID-19 outbreaks. The findings showed that imported infections are dominated by locally transmitted cases. The high incidence was predominant in urban areas and at the borders of Rwanda with its neighboring countries. The inter-district spread of COVID-19 was very limited due to mitigation measures taken in Rwanda.

CONCLUSION

The study recommends using evidence-based decisions in the management of epidemics and integrating statistical models in the analytics component of the health information system.

Community engagement in epigenomic and neurocognitive research on post-traumatic stress disorder in Rwandans exposed to the 1994 genocide against the Tutsi: lessons learned

Epigenomic and neurocognitive studies have provided new perspectives on post-traumatic stress disorder and its intergenerational transmission. This article outlines the lessons learned from community engagement (CE) in such research on Rwandan genocide survivors. A strong trauma-related response was observed within the research project-targeted community (genocide survivors) during explanation of the project. CE also revealed privacy concerns, as community members worried that any leakage of genetic/(epi)genomic data could affect not only themselves but also their close relatives. Adopting a culture of CE in the process of research implementation enables the prioritization of targeted community needs and interests. Furthermore, CE has stimulated the development of mental healthcare interventions, which married couples can apply to protect their offspring and thus truly break the cycle of inherited vulnerability.

Leveraging artificial intelligence and data science techniques in harmonizing, sharing, accessing and analyzing SARS-COV-2/COVID-19 data in Rwanda (LAISDAR Project): study design and rationale

Background

Since the outbreak of COVID-19 pandemic in Rwanda, a vast amount of SARS-COV-2/COVID-19-related data have been collected including COVID-19 testing and hospital routine care data. Unfortunately, those data are fragmented in silos with different data structures or formats and cannot be used to improve understanding of the disease, monitor its progress, and generate evidence to guide prevention measures. The objective of this project is to leverage the artificial intelligence (AI) and data science techniques in harmonizing datasets to support Rwandan government needs in monitoring and predicting the COVID-19 burden, including the hospital admissions and overall infection rates.

Methods

The project will gather the existing data including hospital electronic health records (EHRs), the COVID-19 testing data and will link with longitudinal data from community surveys. The open-source tools from Observational Health Data Sciences and Informatics (OHDSI) will be used to harmonize hospital EHRs through the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The project will also leverage other OHDSI tools for data analytics and network integration, as well as R Studio and Python. The network will include up to 15 health facilities in Rwanda, whose EHR data will be harmonized to OMOP CDM.

Expected results

This study will yield a technical infrastructure where the 15 participating hospitals and health centres will have EHR data in OMOP CDM format on a local Mac Mini (“data node”), together with a set of OHDSI open-source tools. A central server, or portal, will contain a data catalogue of participating sites, as well as the OHDSI tools that are used to define and manage distributed studies. The central server will also integrate the information from the national Covid-19 registry, as well as the results of the community surveys. The ultimate project outcome is the dynamic prediction modelling for COVID-19 pandemic in Rwanda.

Discussion

The project is the first on the African continent leveraging AI and implementation of an OMOP CDM based federated data network for data harmonization. Such infrastructure is scalable for other pandemics monitoring, outcomes predictions, and tailored response planning.

Low COVID-19–related knowledge and access to adequate handwashing among patients with chronic diseases in rural Rwanda: a cross-sectional survey

Background

The coronavirus disease 2019 (COVID-19) misinformation and inadequate access to hygiene and sanitation amenities could hamper efforts to contain COVID-19 spread in resource-limited settings. In this study, we describe knowledge of COVID-19 symptoms and preventive measures, sources of information, and access to adequate handwashing among patients with chronic diseases in three Rwandan rural districts during the onset of COVID-19 in Rwanda.

Methods

This was a cross-sectional survey conducted among patients who were enrolled in the HIV/AIDS, non-communicable diseases, mental health, oncology, and pediatric development programs at health facilities in Kayonza, Kirehe and Burera districts. The study sample was randomly selected and stratified by district and clinical program. Telephone-based data collection occurred between 23 April and 11 May 2020. Primary caregivers responded to the survey when the selected patient was a child under age 18 or severely ill. We defined good knowledge of COVID-19 symptoms and preventive measures as knowing that a dry cough and fever were common symptoms and social distancing or staying home and regular handwashing could prevent COVID-19 infection. Access to adequate handwashing was defined as living in a household with a handwashing station and regular access to clean water and soap. We used Fisher’s exact tests and logistic regression to measure associations between the source of information and good knowledge about COVID-19 and between socio-economic characteristics and access to adequate handwashing.

Results

In total, 150 patients and 70 caregivers responded to the survey. Forty-eight (22.3%) respondents had no formal education. Sources of COVID-19 information included mass media (86.8%), local government leaders (27.3%), healthcare workers (15.9%) and social media (6.8%). Twenty-seven percent (n=59) of respondents had good knowledge of COVID-19 symptoms and preventive measures. In the adjusted analysis, getting information from news media was associated with having good knowledge about COVID-19 (adjusted odds ratio, aOR: 5.46; 95% CI: 1.43-20.75]. Seventy-nine (35.9%) respondents reported access to adequate handwashing at home, with access varying significantly by the district in favour of Kayonza (61.3%).

Conclusions

COVID-19-related knowledge and access to adequate handwashing were low among patients with chronic diseases at the beginning of the pandemic in Rwanda. Efforts to mitigate COVID-19 spread among chronic care populations may include investment in targeted COVID-19-related education and access to adequate handwashing.

Impact of COVID-19 Lock-Downs on Nature Connection in Southern and Eastern Africa

The response of African countries immediately after the COVID-19 pandemic declaration was rapid and appropriate, with low infections and mortality rates until June 2020. Severe lock-down measures were effective in Africa; however, the reduction in the amount of natural experience influences the quality of life in modern society. This study is conducted as an international comparative study in five African countries on changes in the perception of health recovery and outdoor activities in urban forests during the COVID-19 pandemic. An online survey was conducted with 430 respondents to investigate the relationships between COVID-19 stress, indoor activity, appreciation of greenspaces, perception of health recovery, and use of greenspaces. A structural equation model was used for analysis. The visit frequency and staying time in urban forests after lock-down dramatically decreased, raising concerns about nature-deficit disorder across the target countries after the end of the pandemic. This study confirmed urban dwellers’ desire for natural experiences and health recovery during the pandemic and predicts an explosive increase in urban forest utilization after the pandemic has ended.

The basic reproduction number of COVID-19 across Africa

The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) took the world by surprise. Following the first outbreak of COVID-19 in December 2019, several models have been developed to study and understand its transmission dynamics. Although the spread of COVID-19 is being slowed down by vaccination and other interventions, there is still a need to have a clear understanding of the evolution of the pandemic across countries, states and communities. To this end, there is a need to have a clearer picture of the initial spread of the disease in different regions. In this project, we used a simple SEIR model and a Bayesian inference framework to estimate the basic reproduction number of COVID-19 across Africa. Our estimates vary between 1.98 (Sudan) and 9.66 (Mauritius), with a median of 3.67 (90% CrI: 3.31-4.12). The estimates provided in this paper will help to inform COVID-19 modeling in the respective countries/regions.

Effects of SARS-CoV-2 pandemic on follow-up and pharmacological treatment of chronic diseases in undocumented migrants

Background

All over the world, the COVID-19 pandemic, not unlikely other epidemics, has hit harder people in low socioeconomic conditions.

In Western countries, undocumented migrants are a growing component of this disadvantaged segment of the population.

Their health conditions are frequently burdened by a number of chronic conditions, and they experience many difficulties in accessing public health services. Frequently, the only medical assistance they can get is provided by non-governmental organisations.

Methods

We studied the medical records (including pharmacological treatments) of all patients attending the outpatient clinics of Opera San Francesco (OSF; a big charity in Milano, Italy), in the first 5 months of 2020. These comprise the outbreak of the pandemic and the lockdown period. The 1914 patients (1814 undocumented migrants and 100 Italians) seen during the lockdown were compared with those seen in the same period of 2019 and with those seen in the preceding months of 2020. We especially focused on three chronic conditions: cardiovascular diseases, diabetes and psychiatric disorders.

Results

The number of consultations during the first 5 months of 2020 was much smaller than that of the same period of 2019. During the lockdown, we found 4048 consultations for 1914 patients, while they were 8051 in the same period of 2019 and 5681 in the first 2 months of 2020.

The quantity of medicines dispensed by OSF showed a marked decrease in the period of the study and mainly during the lockdown.

The decrease in consultations and dispensation of medicines was most evident for psychiatric patients and almost not existent for patients with diabetes. Female patients suffered a more pronounced reduction.

Conclusions

Western countries need strategies to better assist the very poor during epidemics.

Differences among different groups of disadvantaged persons should be taken into account when designing recovery plans.

The Determinants of the Low COVID-19 Transmission and Mortality Rates in Africa: A Cross-Country Analysis

Background: More than 1 year after the beginning of the international spread of coronavirus 2019 (COVID-19), the reasons explaining its apparently lower reported burden in Africa are still to be fully elucidated. Few studies previously investigated the potential reasons explaining this epidemiological observation using data at the level of a few African countries. However, an updated analysis considering the various epidemiological waves and variables across an array of categories, with a focus on African countries might help to better understand the COVID-19 pandemic on the continent. Thus, we investigated the potential reasons for the persistently lower transmission and mortality rates of COVID-19 in Africa.

Methods: Data were collected from publicly available and well-known online sources. The cumulative numbers of COVID-19 cases and deaths per 1 million population reported by the African countries up to February 2021 were used to estimate the transmission and mortality rates of COVID-19, respectively. The covariates were collected across several data sources: clinical/diseases data, health system performance, demographic parameters, economic indicators, climatic, pollution, and radiation variables, and use of social media. The collinearities were corrected using variance inflation factor (VIF) and selected variables were fitted to a multiple regression model using the R statistical package.

Results: Our model (adjusted R-squared: 0.7) found that the number of COVID-19 tests per 1 million population, GINI index, global health security (GHS) index, and mean body mass index (BMI) were significantly associated (P < 0.05) with COVID-19 cases per 1 million population. No association was found between the median life expectancy, the proportion of the rural population, and Bacillus Calmette–Guérin (BCG) coverage rate. On the other hand, diabetes prevalence, number of nurses, and GHS index were found to be significantly associated with COVID-19 deaths per 1 million population (adjusted R-squared of 0.5). Moreover, the median life expectancy and lower respiratory infections rate showed a trend towards significance. No association was found with the BCG coverage or communicable disease burden.

Conclusions: Low health system capacity, together with some clinical and socio-economic factors were the predictors of the reported burden of COVID-19 in Africa. Our results emphasize the need for Africa to strengthen its overall health system capacity to efficiently detect and respond to public health crises.