Analysis of COVID-19 mathematical model for predicting the impact of control measures in Rwanda.

This paper shows the impact of control measures on the predictive COVID-19 mathematical model in Rwanda through sensitivity analysis of the basic reproduction number R 0 . We have introduced different levels of the control measures in the model, precisely, 90%, 80%, 60%, 40%, 20%, 0% and studied their effects on the variation of the model variables. The results from numerical simulations reveal that the more the adherence to the control measures at the percentage of 90%, 80%, 60%, 40%, 20%, 0%, the more the number of COVID-19 cases, hospitalized and deaths reduces which indicates the reduction of the spread of the pandemic in Rwanda. Moreover, It was shown that the transition rate from the infectious compartment is very sensitive to R 0 as the increase/decrease in its value increases/decreases the value of R 0 and this leads to the high spread or the containment of the pandemic respectively.

Compartmental mathematical modelling of dynamic transmission of COVID-19 in Rwanda.

Objectives: Mathematical modelling is of interest to study the dynamics of coronavirus disease 2019 (COVID-19), and models such as SEIR (Susceptible-Exposed-Infected-Recovered) have been considered. This article describes the development of a compartmental transmission network model - Susceptible-Exposed-Quarantine-Infectious-Infectious, undetected-Infectious, home-based care-Hospitalized-Vaccinated-Recovered-Dead - to simulate the dynamics of COVID-19 in order to account for specific measures put into place by the Government of Rwanda to prevent further spread of the disease. Methods: The compartments of this model are connected by parameters, some of which are known from the literature, and others are estimated from available data using the least squares method. For the stability of the model, equilibrium points were determined and the basic reproduction number R 0 was studied; R 0 is an indicator for contagiousness. Results: The model showed that secondary infections are generated from the exposed group, the asymptomatic group, the infected (symptomatic) group, the infected (undetected) group, the infected (home-based care) group and the hospitalized group. The formulated model was reliable and fit the data. Furthermore, the estimated R 0 of 2.16 shows that COVID-19 will persist without the application of control measures. Conclusions: This article presents results regarding predicted spread of COVID-19 in Rwanda.

Factors Associated with COVID-19 Vaccine Hesitancy in Uganda: A Population-Based Cross-Sectional Survey.

Purpose: Vaccination toward coronavirus disease (COVID-19) has been recommended and adopted as one of the measures of reducing the spread of this novel disease worldwide. Despite this, vaccine uptake among the Ugandan population has been low with reasons surrounding this being unknown. This study aimed to investigate the factors associated with COVID-19 vaccine hesitancy in Uganda. Methods: A cross-sectional study was conducted on a total of 1042 adults in the districts of Mukono, Kiboga, Kumi, Soroti, Gulu, Amuru, Mbarara and Sheema from June to November 2021. Data were analyzed using STATA v.15. Barriers to vaccination were analyzed descriptively, while a binary logistic regression model was used to establish the factors associated with COVID-19 vaccine hesitancy. Results: Overall, COVID-19 vaccine hesitancy was 58.6% (611). Respondents from urban areas and those in the eastern or northern region had increased odds of vaccine hesitancy. Further, higher education level and having knowledge on how COVID-19 is transmitted significantly reduced the odds of vaccine hesitancy. The study also noted individual perception such as COVID-19 kills only people with underlying medical conditions, as well as limited awareness on vaccine types or vaccination areas as the main reasons to vaccine hesitancy. Relatedly, other misconceptions like the ability of the vaccine to cause infertility, or spreading the virus into the body, and acknowledgment of alcohol as a possible cure were other reasons for vaccine hesitancy. Conclusion: The proportion of COVID-19 vaccine hesitancy is still high among the population with this varying across regions. This is driven by low education level and limited awareness on the vaccination as well as perceived myths and misconceptions. The study recommends mass sensitization of the population on the benefits of vaccination using various channels as well as rolling out community-based outreach vaccination campaigns across the country.

Modelling allocation of resources in prevention and control of obstetric fistula in Ugandan women.

In spite of reliable and skilled healthcare resources, the prevalence rate of obstetric fistula in Uganda is high. The risk factors for obstetric fistula cut across due to high poverty rates and cultural barriers. The main objective of this study was to assess the impact of inability to access skilled healthcare at delivery and implications to the economy. The specific objective was to determine the best way of investment in getting women access to skilled healthcare before, during and after child birth. The question to be answered was whether it was more economical to invest in getting women access to skilled healthcare, or in expanding healthcare. The study was conducted using data from the Uganda Demographic Health Survey 2016. The data was from 18,506 women in the age group of 15-49 in 15 regions around the country. Results show that the highest investment in providing access to skilled healthcare is required when there are few skilled healthcare centres. On the other hand, if there is little investment in providing access to skilled healthcare during child birth, many skilled healthcare centres are required. Results show further that the minimum time taken to reduce fistula prevalence is attained when there are many women accessing skilled healthcare in the few equipped health centres. However, if there are many skilled healthcare centres but a few women treated for obstetric fistula, then it will take longer to reduce fistula prevalence. Fitting the model to data suggested that Uganda has a big backlog of women to treat for obstetric fistula as in all skilled healthcare centres, there were less women treated than expected. Although still under the expected figure, the benefit of these treatments for obstetric fistula is that for every one woman treated, 8 more would seek treatment for the condition. This would however cost the country a great deal in that the treatment funds would perhaps give more returns if diverted to outreach activities aimed to get women seek skilled healthcare during child birth.

Modelling optimal allocation of resources in the context of an incurable disease.

Nodding syndrome has affected and led to the deaths of children between the ages of 5 and 15 in Northern Uganda since 2009. There is no reliable explanation of the disease, and currently the only treatment is through a nutritional programme of vitamins, combined with medication to prevent symptoms. In the absence of a proper medical treatment, we develop a dynamic compartmental model to plan the management of the syndrome and to curb its effects. We use incidence data from 2012 and 2013 from Pader, Lamwo and Kitgum regions of Uganda to parameterize the model. The model is then used to look at how to best plan the nutritional programme in terms of first getting children on to the programme through outreach, and then making sure they remain on the programme, through follow-up. For the current outbreak of nodding disease, we estimate that about half of available resources should be put into outreach. We show how to optimize the balance between outreach and follow-up in this particular example, and provide a general methodology for allocating resources in similar situations. Given the uncertainty of parameter estimates in such situations, we perform a robustness analysis to identify the best investment strategy. Our analysis offers a way of using available data to determine the best investment strategy of controlling nodding syndrome.

The dynamics, causes and possible prevention of Hepatitis E outbreaks.

Rapidly spreading infectious diseases are a serious risk to public health. The dynamics and the factors causing outbreaks of these diseases can be better understood using mathematical models, which are fit to data. Here we investigate the dynamics of a Hepatitis E outbreak in the Kitgum region of northern Uganda during 2007 to 2009. First, we use the data to determine that R0 is approximately 2.25 for the outbreak. Secondly, we use a model to estimate that the critical level of latrine and bore hole coverages needed to eradicate the epidemic is at least 16% and 17% respectively. Lastly, we further investigate the relationship between the co-infection factor for malaria and Hepatitis E on the value of R0 for Hepatitis E. Taken together, these results provide us with a better understanding of the dynamics and possible causes of Hepatitis E outbreaks.