Rabies is a zoonotic viral disease that can occur in all warm-blooded animals, including humans. Vaccinating dogs can protect people from contracting rabies. Rabies is a public health threat in Rwanda, but the country does not have information on the epidemiology of rabies. The present study aimed to understand the knowledge, attitudes and practices (KAP) of rabies and its control among dog owners in Kigali city of Rwanda. We conducted a cross-sectional survey using a structured questionnaire among 137 dog owners selected from nine administrative study sites. A two-stage random sampling procedure was used to select the participants. Frequency distributions analysis and a series of chi-square tests of associations as well as binary logistic regressions were performed to determine the important factors associated with the response variables. The results showed that 99.5% of respondents knew at least a host susceptible to rabies. Only 22.4% and 21.3% knew that dogs and people can develop rabies, respectively. Nearly 73.6% knew that human rabies can be transmitted through dog-bites and 99% could identify at least a clinical sign of canine rabies. Overall, 81.8% knew that regular vaccination of dogs helps to prevent dog-transmitted human rabies and 43.1% and 26.3% were aware that rabies in humans and in dogs are fatal once clinical symptoms have shown, respectively. Only 69% would observe a dog for 10 days after it bites a man or an animal. Approximately 20.4% were familiar with appropriate cleaning of dog-bites wounds, and 20.6% knew that puppies could receive rabies vaccination before they are three months old. Of those who owned vaccinated dogs, 78% were happy about the cost (US $ ≤ 34) of rabies vaccination. Of all the respondents, 58% had their dogs vaccinated at home by veterinarians while 86% indicated their veterinarians kept rabies vaccines on ice in a cool box. Overall, 53% of the dog owners had sufficient knowledge of rabies, whilst 66% and 17% adopted adequate practices and positive attitudes towards rabies, respectively. Multivariable logistic regression analyses indicated that none of the respondents’ sex, educational level, and the length of dog ownership were statistically associated with their knowledge, attitudes and practices of rabies. This study showed that majority of the dog owners had sufficient knowledge and adopted appropriate practices of rabies. However there exist some knowledge gaps among the dog owners particularly on treatment, transmission and control methods. Therefore, rabies awareness campaign is required to upgrade rabies knowledge of the dog owners on rabies prevention and control in Rwanda.

Every year, 435,000 people worldwide die from Malaria, mainly in Africa and Asia. However, malaria is a curable and preventable disease. Most countries are developing malaria elimination plans to meet sustainable development goal three, target 3.3, which includes ending the epidemic of malaria by 2030. Rwanda, through the malaria strategic plan 2012-2018 set a target to reduce malaria incidence by 42% from 2012 to 2018. Assessing the health policy and taking a decision using the incidence rate approach is becoming more challenging. We are proposing suitable statistical methods that handle spatial structure and uncertainty on the relative risk that is relevant to National Malaria Control Program. We used a spatio-temporal model to estimate the excess probability for decision making at a small area on evaluating reduction of incidence. SIR and BYM models were developed using routine data from Health facilities for the period from 2012 to 2018 in Rwanda. The fitted model was used to generate relative risk (RR) estimates comparing the risk with the malaria risk in 2012, and to assess the probability of attaining the set target goal per area. The results showed an overall increase in malaria in 2013 to 2018 as compared to 2012. Ofall sectors in Rwanda, 47.36% failed to meet targeted reduction in incidence from 2012 to 2018. Our approach of using excess probability method to evaluate attainment of target or identifying threshold is a relevant statistical method, which will enable the Rwandan Government to sustain malaria control and monitor the effectiveness of targeted interventions.

Pharmaceuticals account for a large portion of healthcare spending in healthcare organizations. Their effective inventory management is required to match the cost of stocks with the customer demand and avoid shortage of supplies at any health facility level. This study aimed to analyze pharmaceuticals' inventory management using ABC-VEN analysis. The study was conducted at Rwanda Medical Supply (RMS) Ltd, Nyamagabe Branch for products distributed to health facilities in Nyamagabe District catchment area from the financial years 2017–2018 to 2019–2020. It consisted of a descriptive retrospective study of 457 items. The latter are generic essential medicines distributed to public health facilities during the study period. Products were arranged according to a descending order of importance, and we performed a breakdown of products according to the Pareto Principle. Following an ABC analysis of distribution data for such drugs billed to healthcare facilities, a VEN analysis was performed to identify high-value vital products that require more attention. During the ABC analysis, 76 products were classified in group A. These accounted for 19.84% and had a value of 74.91% of the total cost of all products. Group B included 116 products, representing 30.29% with a value of 20% of the total cost, while Group C had 191 products, representing 49.87% with a value of only 5.09% of the total cost. During the VEN analysis, 202 products (44.20%) were classified as vital, 231 (50.54%) as essential, and 24 products (75.26%) as non-vital. The analysis with ABC-VEN resulted in Class I representing 55.80% of all medicines that cost 87.88% of all total cost, Class II representing 40.70% with a total cost of 11.82%, and Class III representing 3.50% with a cost of 0.3%. This study results show that inventory management of vital and expensive products, such as antibiotics, antihypertensive pharmaceuticals, consumables, and massive solutions would be carefully monitored to prevent a shortage of such products at health facility levels. The ABC-VEN analysis is one of the practical and affordable method to achieve their optimized supply chain.

HIV prevalence is rising and has been consistently higher among women in Rwanda whereas a decreasing national HIV prevalence rate in the adult population has stabilised since 2005. Factors explaining the increased vulnerability of women to HIV infection are not currently well understood. A statistical mapping at smaller geographic units and the identification of key HIV risk factors are crucial for pragmatic and more efficient interventions. The data used in this study were extracted from the 2010 Rwanda Demographic and Health Survey data for 6952 women. A full Bayesian geo-additive logistic regression model was fitted to data in order to assess the effect of key risk factors and map district-level spatial effects on the risk of HIV infection. The results showed that women who had STIs, concurrent sexual partners in the 12 months prior to the survey, a sex debut at earlier age than 19 years, were living in a woman-headed or high-economic status household were significantly associated with a higher risk of HIV infection. There was a protective effect of high HIV knowledge and perception. Women occupied in agriculture, and those residing in rural areas were also associated with lower risk of being infected. This study provides district-level maps of the variation of HIV infection among women of child-bearing age in Rwanda. The maps highlight areas where women are at a higher risk of infection; the aspect that proximate and distal factors alone could not uncover. There are distinctive geographic patterns, although statistically insignificant, of the risk of HIV infection suggesting potential effectiveness of district specific interventions. The results also suggest that changes in sexual behaviour can yield significant results in controlling HIV infection in Rwanda.

BackgroundResolution of public health problems in Africa remains a challenge because of insufficient skilled human resource capacity. The Consortium for Advanced Research Training in Africa (CARTA) was established to enhance capacity in multi-disciplinary health research that will make a positive impact on population health in Africa.ObjectiveThe first cohort of the CARTA program describes their perspectives and experiences during the 4 years of fellowship and puts forward suggestions for future progress and direction of research in Africa.ConclusionsThe model of training as shown by the CARTA program is an effective model of research capacity building in African academic institutions. An expansion of the program is therefore warranted to reach out to more African academics in search of advanced research training.

Introduction COVID-19 has shown an exceptionally high spread rate across and within countries worldwide. Understanding the dynamics of such an infectious disease transmission is critical for devising strategies to control its spread. In particular, Rwanda was one of the African countries that started COVID-19 preparedness early in January 2020, and a total lockdown was imposed when the country had only 18 COVID-19 confirmed cases known. Using intensive contact tracing, several infections were identified, with the majority of them being returning travellers and their close contacts. We used the contact tracing data in Rwanda for understanding the geographic patterns of COVID-19 to inform targeted interventions. Methods We estimated the attack rates and identified risk factors associated to COVID-19 spread. We used Bayesian disease mapping models to assess the spatial pattern of COVID-19 and to identify areas characterised by unusually high or low relative risk. In addition, we used multiple variable conditional logistic regression to assess the impact of the risk factors. Results The results showed that COVID-19 cases in Rwanda are localised mainly in the central regions and in the southwest of Rwanda and that some clusters occurred in the northeast of Rwanda. Relationship to the index case, being male and coworkers are the important risk factors for COVID-19 transmission in Rwanda. Conclusion The analysis of contact tracing data using spatial modelling allowed us to identify high-risk areas at subnational level in Rwanda. Estimating risk factors for infection with SARS-CoV-2 is vital in identifying the clusters in low spread of SARS-CoV-2 subnational level. It is imperative to understand the interactions between the index case and contacts to identify superspreaders, risk factors and high-risk places. The findings recommend that self-isolation at home in Rwanda should be reviewed to limit secondary cases from the same households and spatiotemporal analysis should be introduced in routine monitoring of COVID-19 in Rwanda for policy making decision on real time.