RESUMO
This study in Rwanda offers a comprehensive analysis of water quality, reliability, and cost-effectiveness, departing from previous research by utilizing panel data analysis for a nuanced understanding of spatiotemporal dynamics. Unlike earlier studies focusing on specific aspects, this research adopts a holistic approach, examining factors crucial for water supply, quality, and cost, thus providing an integrated view of Rwanda's water sector. By analyzing data from various sources, including the Water and Sanitation Corporation (WASAC), the study evaluates the reliability, quality, and cost-effectiveness of drinking water. It identifies cost-effective water treatment plants and studies determinants such as production cost, raw water quality, and supply between 2017 and 2022, introducing novel metrics such as performance scores and a drinking water quality index. Despite an increase in lost water, WASAC notably improves water supply, resulting in a higher water access rate by 2022. The study highlights the influence of factors such as performance scores and raw water quality on water supply and quality. It emphasizes continuous monitoring, targeted interventions, and community engagement for sustainable water service delivery. The findings provide actionable insights for policymakers, stakeholders, and practitioners, aiming to enhance water management strategies and improve water access in Rwanda.
Assuntos
Água Potável , Qualidade da Água , Abastecimento de Água , Ruanda , Água Potável/análise , Análise Custo-Benefício , Purificação da Água/métodos , Análise de Dados , HumanosRESUMO
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.
Assuntos
COVID-19 , SARS-CoV-2 , Inteligência Artificial , COVID-19/epidemiologia , Teste para COVID-19 , Ciência de Dados , Humanos , Pandemias/prevenção & controle , Ruanda/epidemiologiaRESUMO
OBJECTIVE: To assess the level of compliance with COVID-19 preventive measures and compliance-associated factors in the Rwanda community. DESIGN: Cross-sectional study. SETTINGS: Country-wide community survey in Rwanda. PARTICIPANTS: 4763 participants were randomly sampled following the sampling frame used for the recent Rwanda Demographic Health Survey. Participants were aged between 22 years and 94 years. OUTCOMES: The participants' compliance with three preventive measures (wearing a face mask, washing hands and social distancing) was the main outcome. METHODS: From 14 February 2022 to 27 February 2022, a cross-sectional survey using telephone calls was conducted. Study questionnaires included different questions such as participants' demographics and compliance with COVID-19 preventives measures. Verbal consent was obtained from each participant. The compliance on three main preventive measures (wearing a mask, washing hands and social distancing) were the main outcomes. Univariate and multivariable logistic regression analyses were performed to evaluate factors associated with compliance (age, gender, level of education, socioeconomic status). RESULTS: Compliance with the three primary preventive measures (washing hands 98%, wearing a mask 97% and observing social distance 98%) was at a rate of 95%. The respondents' mean age was 46±11 SD (range 22-98) years. In addition, 69% were female and 86% had attended primary education. Bivariate and regression analyses indicated a significant association among the three primary preventive measures (p<0.05). The results showed factors associated significantly between the different models (p<0.05): proper mask use and social distancing in the hand washing model; hand washing, social distancing, avoiding handshakes and not attending gatherings in the proper mask use model; hand washing and avoiding handshakes in the social distancing model. CONCLUSION: Compliance with the three key preventive measures against COVID-19 was high in the Rwandan community and these measures were interdependent. Therefore, the importance of all three measures should be emphasised for effective disease control.
Assuntos
COVID-19 , Desinfecção das Mãos , Máscaras , Distanciamento Físico , SARS-CoV-2 , Humanos , COVID-19/prevenção & controle , COVID-19/epidemiologia , Ruanda/epidemiologia , Feminino , Adulto , Masculino , Estudos Transversais , Pessoa de Meia-Idade , Máscaras/estatística & dados numéricos , Idoso , Adulto Jovem , Idoso de 80 Anos ou mais , Inquéritos e Questionários , Cooperação do Paciente/estatística & dados numéricosRESUMO
BACKGROUND: Stunting among children under 5 years of age remains a worldwide concern, with 148.1 million (22.3%) stunted in 2022. The recent 2019/2020 Rwanda Demographic Health Survey (RDHS) revealed that the prevalence of stunting in Rwanda among under five children was 33.5%. In Rwanda, there is no sufficient evidence on stunting status to guide prioritized interventions at the sector level, the lowest administrative unit for implementing development initiatives. This study aimed to provide reliable estimates of stunting prevalence in Rwanda at the sector level. METHODS: In this article, Small Area Estimation (SAE) techniques were used to provide sector level estimates of stunting prevalence in children under five in Rwanda. By plugging in relevant significant covariates in the generalized linear mixed model, model-based estimates are produced for all sectors with their corresponding Mean Square Error (MSE). RESULTS: The findings showed that, overall, 40 out of 416 sectors had met the national target of having a stunting rate less than or equal to 19%, while 194 sectors were far from meeting this target, having a stunting rate higher than the national prevalence of 33.5% in the year 2020. The majority of the sectors with stunting prevalence that were higher than the national average of 33.5% were found in the Northern Province with 68 sectors out of 89 and in Western Province with 64 sectors out of 96. In contrast, the prevalence of stunting was lower in the City of Kigali where 14 out of 35 sectors had a stunting rate between 0 and 19%, and all sectors were below the national average. This study showed a substantial connection between stunting and factors such as household size, place of residence, the gender of the household head, and access to improved toilet facilities and clean water. CONCLUSION: The results of this study may guide and support informed policy decisions and promote localised and targeted interventions in Rwanda's most severely affected sectors with a high stunting prevalence in Rwanda.