Building Data Triangulation Capacity for Routine Immunization and Vaccine Preventable Disease Surveillance Programs to Identify Immunization Coverage Inequities.

The Expanded Programme on Immunization (EPI) and Vaccine Preventable Disease (VPD) Surveillance (VPDS) programs generate multiple data sources (e.g., routine administrative data, VPD case data, and coverage surveys). However, there are challenges with the use of these siloed data for programmatic decision-making, including poor data accessibility and lack of timely analysis, contributing to missed vaccinations, immunity gaps, and, consequently, VPD outbreaks in populations with limited access to immunization and basic healthcare services. Data triangulation, or the integration of multiple data sources, can be used to improve the availability of key indicators for identifying immunization coverage gaps, under-immunized (UI) and un-immunized (zero-dose (ZD)) children, and for assessing program performance at all levels of the healthcare system. Here, we describe the data triangulation processes, prioritization of indicators, and capacity building efforts in Bangladesh, Nigeria, and Rwanda. We also describe the analyses used to generate meaningful data, key indicators used to identify immunization coverage inequities and performance gaps, and key lessons learned. Triangulation processes and lessons learned may be leveraged by other countries, potentially leading to programmatic changes that promote improved access and utilization of vaccination services through the identification of UI and ZD children.

Lessons Learned from Sudan Ebola Virus Disease (SUDV) Preparedness in Rwanda: A Comprehensive Review and Way Forward.

BACKGROUND: Ebola Virus Disease (EVD) is a severe and often fatal illness that affects humans and has significant public health implications, including high mortality rates, strain on healthcare systems, and social and economic disruption. On 20 September 2022, Uganda declared an Ebola disease outbreak caused by the Sudan ebolavirus species. The neighboring countries of Uganda were classified by World Health Organization (WHO) as being at high risk of Sudan Ebola Virus Disease (SUDV) importation. The country of Rwanda implemented different sustainable strategies and activities to prepare and ensure a timely and effective response to SUDV outbreaks once it has arrived in the country. We aimed to highlight the sustainable strategies and activities implemented for SUDV preparedness and the subsequent lessons learnt in Rwanda. METHODS: This paper reviewed the documentation on activities implemented for SUDV preparedness, with a focus on lessons learned from different countries. The paper analyzed the common themes and highlighted the key components of EVD preparedness in Rwanda after declaration of SUDV outbreak in Uganda. RESULTS: The key components of SUDV preparedness include its readiness assessment in Rwanda, effective coordination, collaboration and leadership mechanisms, enhancing the early detection and surveillance system, effective risk communication and community engagement, capacity building of healthcare providers on case management and infection prevention and control (IPC), and continual preparedness. These components were essential to ensure timely and effective preparation and response to SUDV related outbreaks. CONCLUSION: A multi-sectoral approach involving all stakeholders was necessary to ensure timely and effective preparation and response. Continuous investment in preparedness, strengthening of health systems, and the review of preparedness components provided insights into the best practices for SUDV preparedness, which were essential to prevent future outbreaks and minimize their impact. This will inform other countries about the role of timely development of preparedness plans.

Baseline knowledge and attitudes on COVID-19 among hotels' staff: A cross-sectional study in Kigali, Rwanda.

BACKGROUND: The World Health Organization declared coronavirus disease 2019 (COVID-19) as a global pandemic on the 11th of March, 2020. Hotels and other public establishments have been associated with higher transmission rates. Sensitisation of staff and strengthening of Infection Prevention and Control (IPC) practices in such settings are important interventions. This study assessed the baseline knowledge and attitudes on COVID-19 among hotels' representatives in Kigali, Rwanda. METHODS: A cross-sectional study was conducted among hotels' staff in Kigali in July 2020. A structured questionnaire was self-administered to 104 participants. Baseline knowledge and attitudes were assessed using a number of pre-test questions and mean scores were used to dichotomise the participants' responses as satisfactory or unsatisfactory. RESULTS: All of the 104 hotels' staff completed the self-administered questionnaires. Sixty-seven percent (n = 70) were male and 58% (n = 60) were aged between 30 and 44 years. The satisfactory rate of correct answers was 63%±2.4 (n = 66) on knowledge and 68%±1.7 (n = 71) on attitudes evaluation. Participants with University education were more likely to have satisfactory knowledge (AOR: 2.6, 95% C.I: 1.07-6.58) than those with secondary education or less. The staff working in the front-office (AOR: 0.05; 95% CI 0.01-0.54) and housekeeping (AOR: 0.09; 95% C.I: 0.01-0.87) were less likely to have satisfactory attitudes than those working in the administration. CONCLUSIONS: Hotels' staff based in the capital of Rwanda have shown satisfactory knowledge and attitudes regarding appropriate IPC practices for preventing the COVID-19 transmission. Educational interventions are needed to improve their knowledge and attitudes for better prevention in this setting.

Case Definitions Used During the First 6 Months of the 10th Ebola Virus Disease Outbreak in the Democratic Republic of the Congo - Four Neighboring Countries, August 2018-February 2019.

On August 1, 2018, the Democratic Republic of the Congo (DRC) declared its 10th Ebola virus disease (Ebola) outbreak in an area with a high volume of cross-border population movement to and from neighboring countries. The World Health Organization (WHO) designated Rwanda, South Sudan, and Uganda as the highest priority countries for Ebola preparedness because of the high risk for cross-border spread from DRC (1). Countries might base their disease case definitions on global standards; however, historical context and perceived risk often affect why countries modify and adapt definitions over time, moving toward or away from regional harmonization. Discordance in case definitions among countries might reduce the effectiveness of cross-border initiatives during outbreaks with high risk for regional spread. CDC worked with the ministries of health (MOHs) in DRC, Rwanda, South Sudan, and Uganda to collect MOH-approved Ebola case definitions used during the first 6 months of the outbreak to assess concordance (i.e., commonality in category case definitions) among countries. Changes in MOH-approved Ebola case definitions were analyzed, referencing the WHO standard case definition, and concordance among the four countries for Ebola case categories (i.e., community alert, suspected, probable, confirmed, and case contact) was assessed at three dates (2). The number of country-level revisions ranged from two to four, with all countries revising Ebola definitions by February 2019 after a December 2018 peak in incidence in DRC. Case definition complexity increased over time; all countries included more criteria per category than the WHO standard definition did, except for the "case contact" and "confirmed" categories. Low case definition concordance and lack of awareness of regional differences by national-level health officials could reduce effectiveness of cross-border communication and collaboration. Working toward regional harmonization or considering systematic approaches to addressing country-level differences might increase efficiency in cross-border information sharing.

The national burden of influenza-associated severe acute respiratory illness hospitalization in Rwanda, 2012-2014.

BACKGROUND: Estimates of influenza-associated hospitalization are severely limited in low- and middle-income countries, especially in Africa. OBJECTIVES: To estimate the national number of influenza-associated severe acute respiratory illness (SARI) hospitalization in Rwanda. METHODS: We multiplied the influenza virus detection rate from influenza surveillance conducted at 6 sentinel hospitals by the national number of respiratory hospitalization obtained from passive surveillance after adjusting for underreporting and reclassification of any respiratory hospitalizations as SARI during 2012-2014. The population at risk was obtained from projections of the 2012 census. Bootstrapping was used for the calculation of confidence intervals (CI) to account for the uncertainty associated with all levels of adjustment. Rates were expressed per 100 000 population. A sensitivity analysis using a different estimation approach was also conducted. RESULTS: SARI cases accounted for 70.6% (9759/13 813) of respiratory admissions at selected hospitals: 77.2% (6783/8786) and 59.2% (2976/5028) among individuals aged <5 and ≥5 years, respectively. Overall, among SARI cases tested, the influenza virus detection rate was 6.3% (190/3022): 5.7% (127/2220) and 7.8% (63/802) among individuals aged <5 and ≥5 years, respectively. The estimated mean annual national number of influenza-associated SARI hospitalizations was 3663 (95% CI: 2930-4395-rate: 34.7; 95% CI: 25.4-47.7): 2637 (95% CI: 2110-3164-rate: 168.7; 95% CI: 135.0-202.4) among children aged <5 years and 1026 (95% CI: 821-1231-rate: 11.3; 95% CI: 9.0-13.6) among individuals aged ≥5 years. The estimates obtained from both approaches were not statistically different (overlapping CIs). CONCLUSIONS: The burden of influenza-associated SARI hospitalizations was substantial and was highest among children aged <5 years.

Implementing One Health as an integrated approach to health in Rwanda.

It is increasingly clear that resolution of complex global health problems requires interdisciplinary, intersectoral expertise and cooperation from governmental, non-governmental and educational agencies. 'One Health' refers to the collaboration of multiple disciplines and sectors working locally, nationally and globally to attain optimal health for people, animals and the environment. One Health offers the opportunity to acknowledge shared interests, set common goals, and drive toward team work to benefit the overall health of a nation. As in most countries, the health of Rwanda's people and economy are highly dependent on the health of the environment. Recently, Rwanda has developed a One Health strategic plan to meet its human, animal and environmental health challenges. This approach drives innovations that are important to solve both acute and chronic health problems and offers synergy across systems, resulting in improved communication, evidence-based solutions, development of a new generation of systems-thinkers, improved surveillance, decreased lag time in response, and improved health and economic savings. Several factors have enabled the One Health movement in Rwanda including an elaborate network of community health workers, existing rapid response teams, international academic partnerships willing to look more broadly than at a single disease or population, and relative equity between female and male health professionals. Barriers to implementing this strategy include competition over budget, poor communication, and the need for improved technology. Given the interconnectedness of our global community, it may be time for countries and their neighbours to follow Rwanda's lead and consider incorporating One Health principles into their national strategic health plans.

Influenza sentinel surveillance in Rwanda, 2008-2010.

BACKGROUND: In 2008, Rwanda established an influenza sentinel surveillance (ISS) system to describe the epidemiology of influenza and monitor for the emergence of novel influenza A viruses. We report surveillance results from August 2008 to July 2010. METHODS: We conducted ISS by monitoring patients with influenza-like illness (ILI) and severe acute respiratory infection (SARI) at 6 hospitals. For each case, demographic and clinical data, 1 nasopharyngeal specimen, and 1 oropharyngeal specimen were collected. Specimens were tested by real-time reverse-transcription polymerase chain reaction for influenza A and B viruses at the National Reference Laboratory in Rwanda. RESULTS: A total of 1916 cases (945 ILI and 971 SARI) were identified. Of these, 29.2% (n = 276) of ILI and 10.4% (n = 101) of SARI cases tested positive for influenza. Of the total influenza-positive cases (n = 377), 71.8% (n = 271) were A(H1N1) pdm09, 5.6% (n = 21) influenza A(H1), 7.7% (n = 29) influenza A(H3), 1.6% (n = 6) influenza A (unsubtyped), and 13.3% (n = 50) influenza B. The percentage of positivity for influenza viruses was highest in October-November and February-March, during peaks in rainfall. CONCLUSIONS: The implementation of ISS enabled characterization of the epidemiology and seasonality of influenza in Rwanda for the first time. Future efforts should determine the population-based influenza burden to inform interventions such as targeted vaccination.

2009 pandemic influenza A (H1N1) virus outbreak and response--Rwanda, October, 2009-May, 2010.

BACKGROUND: In October 2009, the first case of pandemic influenza A(H1N1)pdm09 (pH1N1) was confirmed in Kigali, Rwanda and countrywide dissemination occurred within several weeks. We describe clinical and epidemiological characteristics of this epidemic. METHODS: From October 2009 through May 2010, we undertook epidemiologic investigations and response to pH1N1. Respiratory specimens were collected from all patients meeting the WHO case definition for pH1N1, which were tested using CDC's real time RT-PCR protocol at the Rwandan National Reference Laboratory (NRL). Following documented viral transmission in the community, testing focused on clinically severe and high-risk group suspect cases. RESULTS: From October 9, 2009 through May 31, 2010, NRL tested 2,045 specimens. In total, 26% (n = 532) of specimens tested influenza positive; of these 96% (n = 510) were influenza A and 4% (n = 22) were influenza B. Of cases testing influenza A positive, 96.8% (n = 494), 3% (n = 15), and 0.2% (n = 1) were A(H1N1)pdm09, Seasonal A(H3) and Seasonal A(non-subtyped), respectively. Among laboratory-confirmed cases, 263 (53.2%) were children <15 years and 275 (52%) were female. In total, 58 (12%) cases were hospitalized with mean duration of hospitalization of 5 days (Range: 2-15 days). All cases recovered and there were no deaths. Overall, 339 (68%) confirmed cases received oseltamivir in any setting. Among all positive cases, 26.9% (143/532) were among groups known to be at high risk of influenza-associated complications, including age <5 years 23% (122/532), asthma 0.8% (4/532), cardiac disease 1.5% (8/532), pregnancy 0.6% (3/532), diabetes mellitus 0.4% (2/532), and chronic malnutrition 0.8% (4/532). CONCLUSIONS: Rwanda experienced a PH1N1 outbreak which was epidemiologically similar to PH1N1 outbreaks in the region. Unlike seasonal influenza, children <15 years were the most affected by pH1N1. Lessons learned from the outbreak response included the need to strengthen integrated disease surveillance, develop laboratory contingency plans, and evaluate the influenza sentinel surveillance system.

Use of routine data collected by the prevention of mother-to-child transmission program for HIV surveillance among pregnant women in Rwanda: opportunities and limitations.

To compare HIV prevalence measured by antenatal clinics (ANC) sentinel surveillance and by the prevention of mother-to-child transmission (PMTCT) program in Rwanda. We compared HIV prevalence from anonymous testing performed under ANC surveillance, and that measured from voluntary counselling and testing performed under the PMTCT program, in a random sample of the same population of pregnant women attending for their first antenatal visit at 29 ANC surveillance sites with a PMTCT program in 2007 in Rwanda. All of the 13,318 pregnant women recruited in the ANC surveillance accepted to participate in the PMTCT program. HIV prevalence measured by sentinel surveillance was 4.35% whereas that measured for 1873 pregnant women (out of the total sentinel population) by the PMTCT program was 3.49% (p=0.07). For 3% of the PMTCT population, HIV test results were missing from the counselling logbook versus 0.3% in the ANC laboratory logbooks. For 10 pregnant women, HIV test results were divergent between the PMTCT and the ANC laboratory logbooks. After missing data and errors were corrected, HIV prevalence results from PMTCT was 3.27% (significantly different from ANC surveillance: p =0.03). High uptake of PMTCT program among pregnant women was observed in Rwanda in 2007. HIV prevalence measured by the ANC surveillance and PMTCT program were significantly different. Poor performance in HIV testing practices and PMTCT/laboratories data management could explain this difference. Improvement in HIV testing practices and in PMTCT/laboratory data management are needed in order to use PMTCT data for HIV surveillance and to ensure good performance of all the package of care provided by the PMTCT program.

HIV Prevalence Comparison Between Antenatal Sentinel Surveillance and Demographic and Health Survey in Rwanda.

OBJECTIVE: To compare HIV prevalence from antenatal surveillance to that of the demographic and health survey (DHS), and to identify factors determining the difference of HIV prevalence between women recruited in these two surveys in Rwanda in 2005. METHODS: Comparative cross-sectional study of HIV prevalence and socio-demographic factors collected by the antenatal survey in 13,745 pregnant women, seen in 30 health centres located throughout the country and those collected by the DHS among 5641 women, aged 15-49 years living in households located throughout the country. Log-binomial regression and direct standardization were used to estimate and compare HIV prevalence between the two surveys. RESULTS: HIV prevalence in the antenatal survey was slightly higher than that in DHS women (4.1% versus 3.6% p=0.103). Socio-demographic characteristics were differently distributed between the two populations. Whereas, 59%, 93%, 53% of pregnant women were aged 20-29 years, married or cohabiting and living in rural areas respectively, the corresponding proportions among DHS women were 35%, 48% and 83% (p<0.001). Simultaneous standardization of antenatal prevalence according to the distribution of socio-demographic characteristics in the DHS gave an overall HIV prevalence estimate of 3.6%, similar to the prevalence measured among DHS women. CONCLUSIONS: HIV prevalence in the antenatal survey overestimated that among women of the general population in Rwanda in 2005. This overestimation could be corrected by standardization of antenatal prevalence according to the distribution of age, geographical area, marital status, parity, and education, in the general population.