An Assessment of the Knowledge and Perceptions of Precision Medicine (PM) in the Rwandan Healthcare Setting.

INTRODUCTION: Precision medicine (PM) or personalized medicine is an innovative approach that aims to tailor disease prevention and treatment to consider the differences in people's genes, environments, and lifestyles. Although many efforts have been made to accelerate the universal adoption of PM, several challenges need to be addressed in order to advance PM in Africa. Therefore, our study aimed to establish baseline data on the knowledge and perceptions of the implementation of PM in the Rwandan healthcare setting. METHOD: A descriptive qualitative study was conducted in five hospitals offering diagnostics and oncology services to cancer patients in Rwanda. To understand the existing policies regarding PM implementation in the country, two additional institutions were surveyed: the Ministry of Health (MOH), which creates and sets policies for the overall vision of the health sector, and the Rwanda Biomedical Center (RBC), which coordinates the implementation of health sector policies in the country. The researchers conducted 32 key informant interviews and assessed the functionality of available PM equipment in the 5 selected health facilities. The data were thematically categorized and analyzed. RESULTS: The study revealed that PM is perceived as a complex and expensive program by most health managers and health providers. The most cited challenges to implementing PM included the following: the lack of policies and guidelines; the lack of supportive infrastructures and limited suppliers of required equipment and laboratory consumables; financial constraints; cultural, behavioral, and religious beliefs; and limited trained, motivated, and specialized healthcare providers. Regarding access to health services for cancer treatment, patients with health insurance pay 10% of their medical costs, which is still too expensive for Rwandans. CONCLUSION: The study participants highlighted the importance of PM to enhance healthcare delivery if the identified barriers are addressed. For instance, Rwandan health sector leadership might consider the creation of specialized oncology centers in all or some referral hospitals with all the necessary genomic equipment and trained staff to serve the needs of the country and implement a PM program.

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.

Spatio-Temporal Bayesian Models for Malaria Risk Using Survey and Health Facility Routine Data in Rwanda.

INTRODUCTION: Malaria is a life-threatening disease ocuring mainly in developing countries. Almost half of the world's population was at risk of malaria in 2020. Children under five years age are among the population groups at considerably higher risk of contracting malaria and developing severe disease. Most countries use Demographic and Health Survey (DHS) data for health programs and evaluation. However, malaria elimination strategies require a real-time, locally-tailored response based on malaria risk estimates at the lowest administrative levels. In this paper, we propose a two-step modeling framework using survey and routine data to improve estimates of malaria risk incidence in small areas and enable quantifying malaria trends. METHODS: To improve estimates, we suggest an alternative approach to modeling malaria relative risk by combining information from survey and routine data through Bayesian spatio-temporal models. We model malaria risk using two steps: (1) fitting a binomial model to the survey data, and (2) extracting fitted values and using them in the Poison model as nonlinear effects in the routine data. We modeled malaria relative risk among under-five-year old children in Rwanda. RESULTS: The estimation of malaria prevalence among children who are under five years old using Rwanda demographic and health survey data for the years 2019-2020 alone showed a higher prevalence in the southwest, central, and northeast of Rwanda than the rest of the country. Combining with routine health facility data, we detected clusters that were undetected based on the survey data alone. The proposed approach enabled spatial and temporal trend effect estimation of relative risk in local/small areas in Rwanda. CONCLUSIONS: The findings of this analysis suggest that using DHS combined with routine health services data for active malaria surveillance may provide provide more precise estimates of the malaria burden, which can be used toward malaria elimination targets. We compared findings from geostatistical modeling of malaria prevalence among under-five-year old children using DHS 2019-2020 and findings from malaria relative risk spatio-temporal modeling using both DHS survey 2019-2020 and health facility routine data. The strength of routinely collected data at small scales and high-quality data from the survey contributed to a better understanding of the malaria relative risk at the subnational level in Rwanda.

Leveraging Serosurveillance and Postmortem Surveillance to Quantify the Impact of Coronavirus Disease 2019 in Africa.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has had a devastating impact on global health, the magnitude of which appears to differ intercontinentally: For example, reports suggest that 271 900 per million people have been infected in Europe versus 8800 per million people in Africa. While Africa is the second-largest continent by population, its reported COVID-19 cases comprise <3% of global cases. Although social and environmental explanations have been proposed to clarify this discrepancy, systematic underascertainment of infections may be equally responsible. METHODS: We sought to quantify magnitudes of underascertainment in COVID-19's cumulative incidence in Africa. Using serosurveillance and postmortem surveillance, we constructed multiplicative factors estimating ratios of true infections to reported cases in Africa since March 2020. RESULTS: Multiplicative factors derived from serology data (subset of 12 nations) suggested a range of COVID-19 reporting rates, from 1 in 2 infections reported in Cape Verde (July 2020) to 1 in 3795 infections reported in Malawi (June 2020). A similar set of multiplicative factors for all nations derived from postmortem data points toward the same conclusion: Reported COVID-19 cases are unrepresentative of true infections, suggesting that a key reason for low case burden in many African nations is significant underdetection and underreporting. CONCLUSIONS: While estimating the exact burden of COVID-19 is challenging, the multiplicative factors we present furnish incidence estimates reflecting likely-to-worst-case ranges of infection. Our results stress the need for expansive surveillance to allocate resources in areas experiencing discrepancies between reported cases, projected infections, and deaths.

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.

Brief Report: Active HIV Case Finding in the City of Kigali, Rwanda: Assessment of Voluntary Assisted Partner Notification Modalities to Detect Undiagnosed HIV Infections.

BACKGROUND: Voluntary assisted partner notification (VAPN) services that use contract, provider, or dual referral modalities may be efficient to identify individuals with undiagnosed HIV infection. We aimed to assess the relative effectiveness of VAPN modalities in identifying undiagnosed HIV infections. SETTING: VAPN was piloted in 23 health facilities in Kigali, Rwanda. METHODS: We identified individuals with a new HIV diagnosis before antiretroviral therapy initiation or individuals on antiretroviral therapy (index cases), who reported having had sexual partners with unknown HIV status, to assess the association between referral modalities and the odds of identifying HIV-positive partners using a Bayesian hierarchical logistic regression model. We adjusted our model for important factors identified through a Bayesian variable selection. RESULTS: Between October 2018 and December 2019, 6336 index cases were recruited, leading to the testing of 7690 partners. HIV positivity rate was 7.1% (546/7690). We found no association between the different referral modalities and the odds of identifying HIV-positive partners. Notified partners of male individuals (adjusted odds ratio 1.84; 95% credible interval: 1.50 to 2.28) and index cases with a new HIV diagnosis (adjusted odds ratio 1.82; 95% credible interval: 1.45 to 2.30) were more likely to be infected with HIV. CONCLUSION: All 3 VAPN modalities were comparable in identifying partners with HIV. Male individuals and newly diagnosed index cases were more likely to have partners with HIV. HIV-positive yield from index testing was higher than the national average and should be scaled up to reach the first UNAIDS-95 target by 2030.

Experience of Rwanda on COVID-19 Case Management: From Uncertainties to the Era of Neutralizing Monoclonal Antibodies.

The management of COVID-19 in Rwanda has been dynamic, and the use of COVID-19 therapeutics has gradually been updated based on scientific discoveries. The treatment for COVID-19 remained patient-centered and entirely state-sponsored during the first and second waves. From the time of identification of the index case in March 2020 up to August 2021, three versions of the clinical management guidelines were developed, with the aim of ensuring that the COVID-19 patients treated in Rwanda were receiving care based on the most recent therapeutic discoveries. As the case load increased and imposed imminent heavy burdens on the healthcare system, a smooth transition was made to enable that the asymptomatic and mild COVID-19 cases could continue to be closely observed and managed while they remained in their homes. The care provided to patients requiring facility-based interventions mainly focused on the provision of anti-inflammatory drugs, anticoagulation, broad-spectrum antibiotic therapy, management of hyperglycemia and the provision of therapeutics with a direct antiviral effect such as favipiravir and neutralizing monoclonal antibodies. The time to viral clearance was observed to be shortest among eligible patients treated with neutralizing monoclonal antibodies (bamlanivimab). Moving forward, as we strive to continue detecting COVID-19 cases as early as possible, and promptly initiate supportive interventions, the use of neutralizing monoclonal antibodies constitutes an attractive and cost-effective therapeutic approach. If this approach is used strategically along with other measures in place (i.e., COVID-19 vaccine roll out, etc.), it will enable us to bring this global battle against the COVID-19 pandemic under full control and with a low case fatality rate.

Vitamin D Levels in Mother-Baby Pairs: A Cross-Sectional Prospective Study in a Rwandan Tertiary Hospital.

BACKGROUND: Exposure to the sunlight contributes largely to the production of vitamin D. However, vitamin D deficiency is a reality in tropical countries, despite enjoying enough sunlight, especially bearing women in their last trimester whose foetuses exclusively depend on their reserves. This work aimed at demonstrating the state of vitamin D in mother-baby pairs and associated factors in one of the University Hospitals in Rwanda. METHODS: This cross-sectional prospective study was performed on mother-baby pairs at Kigali University Hospital. Mother's serum 25-hydroxyvitamin D levels were considered as outcomes compared with demographic, clinical and biological markers. Correlation analysis was conducted in order to assess the association between serum 25-hydroxyvitamin D levels for the couple mothers-babies. RESULTS: Approximately 38% of women and 65% of neonates had deficiency in 25-hydroxyvitamin D (<20 ng/ml). The use of a vitamin D rich diet within 24 h recall (p < 0.01) or 1 week recall (p < 0.001) before delivery was associated with appropriate vitamin D levels in mothers. Interestingly, a strong positive correlation was found between maternal and neonatal serum 25-hydroxyvitamin D levels (r = 0.760). CONCLUSIONS: There was a high rate of vitamin D deficiency in mothers and their babies. Babies born from women with deficiency were likely to develop low levels of vitamin D. This stresses on the need to strengthen the interventions for preventing vitamin D deficiency in the couple mothers-babies such as supplement in vitamin D before and after delivery, improving the quality of meals and regular contact with sunlight.

The secondary transmission pattern of COVID-19 based on contact tracing in Rwanda.

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.

Child mortality associated with maternal HIV status: a retrospective analysis in Rwanda, 2005-2015.

INTRODUCTION: Child mortality remains highest in regions of the world most affected by HIV/AIDS. The aim of this study was to assess child mortality rates in relation to maternal HIV status from 2005 to 2015, the period of rapid HIV treatment scale-up in Rwanda. METHODS: We used data from the 2005, 2010 and 2015 Rwanda Demographic Health Surveys to derive under-2 mortality rates by survey year and mother's HIV status and to build a multivariable logistic regression model to establish the association of independent predictors of under-2 mortality stratified by mother's HIV status. RESULTS: In total, 12 010 live births were reported by mothers in the study period. Our findings show a higher mortality among children born to mothers with HIV compared with HIV negative mothers in 2005 (216.9 vs 100.7 per 1000 live births) and a significant reduction in mortality for both groups in 2015 (72.0 and 42.4 per 1000 live births, respectively). In the pooled reduced multivariable model, the odds of child mortality was higher among children born to mothers with HIV, (adjusted OR, AOR 2.09; 95% CI 1.57 to 2.78). The odds of child mortality were reduced in 2010 (AOR 0.69; 95% CI 0.59 to 0.81) and 2015 (AOR 0.35; 95% CI 0.28 to 0.44) compared with 2005. Other independent predictors of under-2 mortality included living in smaller families of 1-2 members (AOR 5.25; 95% CI 3.59 to 7.68), being twin (AOR 4.93; 95% CI 3.51 to 6.92) and being offspring from mothers not using contraceptives at the time of the survey (AOR 1.6; 95% CI 1.38 to 1.99). Higher education of mothers (completed primary school: (AOR 0.74; 95% CI 0.64 to 0.87) and secondary or higher education: (AOR 0.53; 95% CI 0.38 to 0.74)) was also associated with reduced child mortality. CONCLUSIONS: This study shows an important decline in under-2 child mortality among children born to both mothers with and without HIV in Rwanda over a 10-year span.

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

The African region was predicted to have worse COVID-19 infection and death rates due to challenging health systems and social determinants of health. However, in the 10 months after its first case, Rwanda recorded 10316 cases and 133 COVID-19-related deaths translating to a case fatality rate (CFR) of 1.3%, which raised the question: why does Rwanda have a low COVID-19 CFR? Here we analysed COVID-19 data and explored possible explanations to better understand the disease burden in the context of Rwanda's infection control strategies.We investigated whether the age distribution plays a role in the observed low CFR in Rwanda by comparing the expected number of deaths for 10-year age bands based on the CFR reported in other countries with the observed number of deaths for each age group. We found that the age-specific CFRs in Rwanda are similar to or, in some older age groups, slightly higher than those in other countries, suggesting that the lower population level CFR reflects the younger age structure in Rwanda, rather than a lower risk of death conditional on age. We also accounted for Rwanda's comprehensive SARS-CoV-2 testing strategies and reliable documentation of COVID-19-related deaths and deduced that these measures may have allowed them to likely identify more asymptomatic or mild cases than other countries and reduced their reported CFR.Overall, the observed low COVID-19 deaths in Rwanda is likely influenced by the combination of effective infection control strategies, reliable identification of cases and reporting of deaths, and the population's young age structure.

The Global Cohort of Doctoral Students: Building Shared Global Health Research Capacity in High-Income and Low- and Middle-Income Countries.

Doctoral students in high- and low-income countries pursuing careers in global health face gaps in their training that could be readily filled through structured peer-learning activities with students based at partnering institutions in complimentary settings. We share lessons learned from the Global Cohort of Doctoral Students, a community of doctoral students based at the Harvard T. H. Chan School of Public Health, Haramaya University, University of Gondar, University of Botswana, and University of Rwanda College of Medicine and Health Sciences. Students in the Global Cohort program engage in collaborative research, forums for constructive feedback, and professional development activities. We describe the motivation for the program, core activities, and early successes.

A pooled testing strategy for identifying SARS-CoV-2 at low prevalence.

Suppressing infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will probably require the rapid identification and isolation of individuals infected with the virus on an ongoing basis. Reverse-transcription polymerase chain reaction (RT-PCR) tests are accurate but costly, which makes the regular testing of every individual expensive. These costs are a challenge for all countries around the world, but particularly for low-to-middle-income countries. Cost reductions can be achieved by pooling (or combining) subsamples and testing them in groups1-7. A balance must be struck between increasing the group size and retaining test sensitivity, as sample dilution increases the likelihood of false-negative test results for individuals with a low viral load in the sampled region at the time of the test8. Similarly, minimizing the number of tests to reduce costs must be balanced against minimizing the time that testing takes, to reduce the spread of the infection. Here we propose an algorithm for pooling subsamples based on the geometry of a hypercube that, at low prevalence, accurately identifies individuals infected with SARS-CoV-2 in a small number of tests and few rounds of testing. We discuss the optimal group size and explain why, given the highly infectious nature of the disease, largely parallel searches are preferred. We report proof-of-concept experiments in which a positive subsample was detected even when diluted 100-fold with negative subsamples (compared with 30-48-fold dilutions described in previous studies9-11). We quantify the loss of sensitivity due to dilution and discuss how it may be mitigated by the frequent re-testing of groups, for example. With the use of these methods, the cost of mass testing could be reduced by a large factor. At low prevalence, the costs decrease in rough proportion to the prevalence. Field trials of our approach are under way in Rwanda and South Africa. The use of group testing on a massive scale to monitor infection rates closely and continually in a population, along with the rapid and effective isolation of people with SARS-CoV-2 infections, provides a promising pathway towards the long-term control of coronavirus disease 2019 (COVID-19).

Bayesian spatio-temporal modeling of malaria risk 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.

Nationwide Remapping of Schistosoma mansoni Infection in Rwanda Using Circulating Cathodic Antigen Rapid Test: Taking Steps toward Elimination.

The field standard for the detection of Schistosoma mansoni infection is Kato-Katz (KK), although it misses many active infections, especially light infections. In 2014, a reassessment of S. mansoni prevalence was conducted in Rwanda using the more sensitive point-of-care circulating cathodic antigen (POC-CCA) rapid assay. A total of 19,371 children from 399 schools were selected for testing for single urine CCA. Of these, 8,697 children from 175 schools were also tested with single stool double-slide KK. Samples from eight of these 175 schools were tested again with CCA and additionally with the highly specific and sensitive up-converting phosphor-lateral flow circulating anodic antigen (UCP-LF CAA) assay. Latent class analysis was applied to all four test results to assess sensitivity and specificity of POC-CCA and estimate the proportion of trace results from Rwanda likely to be true infections. The overall prevalence of S. mansoni infection in Rwanda when CCA trace results were considered negative was 7.4% (school interquartile range [IQR] 0-8%) and 36.1% (school IQR 20-47%) when trace was considered positive. Prevalence by KK was 2.0% with a mean intensity of infection of 1.66 eggs per gram. The proportion of active infections among children diagnosed with CCA trace was estimated by statistical analysis at 61% (Bayesian credibility interval: 50-72%). These results indicate that S. mansoni infection is still widespread in Rwanda and prevalence is much underestimated by KK testing. Circulating cathodic antigen is an affordable alternative to KK and more suitable for measuring S. mansoni prevalence in low-intensity regions.

Retention in care and virological failure among adult HIV+ patients on second-line ART in Rwanda: a national representative study.

BACKGROUND: Currently, there is limited evidence on the effectiveness of second-line antiretroviral therapy (ART) in sub-Saharan Africa. To address this challenge, outcomes of second-line protease inhibitor (PI) based ART in Rwanda were assessed. METHODS: A two-stage cluster sampling design was undertaken. 49 of 340 health facilities linked to the open-source electronic medical record (EMR) system of Rwanda were randomly sampled. Data sampling criteria included adult HIV positive patients with documented change from first to second-line ART regimen. Retention in care and treatment failure (viral load above 1000 copies/mL) were evaluated using multivariable Cox proportional hazards and logistic regression models. RESULTS: A total of 1688 patients (60% females) initiated second-line ART PI-based regimen by 31st December 2016 with a median follow-up time of 26 months (IQR 24-36). Overall, 92.5% of patients were retained in care; 83% achieved VL ≤ 1000 copies/ml, 2.8% were lost to care and 2.2% died. Defaulting from care was associated with more recent initiation of ART- PI based regimen, CD4 cell count ≤500 cells/mm3 at initiation of second line ART and viral load > 1000 copies/ml at last measurement. Viral failure was associated with younger age, WHO stage III&IV at ART initiation, CD4 cell count ≤500 cells/mm3 at switch, atazanavir based second-line ART and receiving care at a health center compared to hospital settings. CONCLUSIONS: A high proportion of patients on second-line ART are doing relatively well in Rwanda and retained in care with low viral failure rates. However, enhanced understandings of adherence and adherence interventions for less healthy individuals are required. Routine viral load measurement and tracing of loss to follow-up is fundamental in resource limited settings, especially among less healthy patients.

A case report of anterior cruciate ligament and posterolateral corner reconstruction using tendon graft preserved in situ.

INTRODUCTION: Combined anterior cruciate ligament (ACL) and posterolateral corner (PLC) reconstruction are a rare clinical entity in orthopedic literature, whose management requires different types of tendon grafts. Missed PLC injury leads to the failure of ACL repair due to the joint instability. PRESENTATION OF CASE: We are presenting a case of posttraumatic right ACL, PLC and lateral meniscus injury. The patient was taken to theatre for arthroscopic meniscectomy, ACL and PLC reconstruction. We had to harvest bilateral Gracilis and semitendinosus tendon grafts. Intraoperatively, we used a pump and after meniscectomy and ACL reconstruction the knee was quite swollen; we opted to offer a two-staged procedure for PLC reconstruction. Hence we had to preserve the graft in situ for the next procedure. Posterolateral corner reconstruction was done in a week's time and preserved ligament was found to be intact. DISCUSSION: The fact that we did not have a tissue bank or facilities for cryopreservation of the harvested tendons at -80 °C or with liquid nitrogen at -179 °C yet we had to keep the harvested tendons safe. CONCLUSION: In case of absence of graft and bone bank, tendon graft was in situ and found intact and ready to be used after seven days.

Applied statistical training to strengthen analysis and health research capacity in Rwanda.

BACKGROUND: To guide efficient investment of limited health resources in sub-Saharan Africa, local researchers need to be involved in, and guide, health system and policy research. While extensive survey and census data are available to health researchers and program officers in resource-limited countries, local involvement and leadership in research is limited due to inadequate experience, lack of dedicated research time and weak interagency connections, among other challenges. Many research-strengthening initiatives host prolonged fellowships out-of-country, yet their approaches have not been evaluated for effectiveness in involvement and development of local leadership in research. METHODS: We developed, implemented and evaluated a multi-month, deliverable-driven, survey analysis training based in Rwanda to strengthen skills of five local research leaders, 15 statisticians, and a PhD candidate. Research leaders applied with a specific research question relevant to country challenges and committed to leading an analysis to publication. Statisticians with prerequisite statistical training and experience with a statistical software applied to participate in class-based trainings and complete an assigned analysis. Both statisticians and research leaders were provided ongoing in-country mentoring for analysis and manuscript writing. RESULTS: Participants reported a high level of skill, knowledge and collaborator development from class-based trainings and out-of-class mentorship that were sustained 1 year later. Five of six manuscripts were authored by multi-institution teams and submitted to international peer-reviewed scientific journals, and three-quarters of the participants mentored others in survey data analysis or conducted an additional survey analysis in the year following the training. CONCLUSIONS: Our model was effective in utilizing existing survey data and strengthening skills among full-time working professionals without disrupting ongoing work commitments and using few resources. Critical to our success were a transparent, robust application process and time limited training supplemented by ongoing, in-country mentoring toward manuscript deliverables that were led by Rwanda's health research leaders.

Determinants of fertility in Rwanda in the context of a fertility transition: a secondary analysis of the 2010 Demographic and Health Survey.

BACKGROUND: Major improvements to Rwanda's health system, infrastructure, and social programs over the last decade have led to a rapid fertility transition unique from other African countries. The total fertility rate fell from 6.1 in 2005 to 4.6 in 2010, with a 3-fold increase in contraceptive usage. Despite this rapid national decline, many women still have large numbers of children. This study investigates predictors of fertility during this fertility transition to inform policies that improve individuals' reproductive health and guide national development. METHODS: We used Poisson regression to separately model number of children born to ever married/cohabitated women (n = 8,309) and never married women (n = 1,220) age 15 to 49 based on 2010 Rwanda Demographic and Health Survey data. We used backward stepwise regression with a time offset to identify individual and household factors associated with woman's fertility level, accounting for sampling weights, clustering, and stratification. RESULTS: In ever married/cohabitating women, high fertility was significantly associated (p < 0.05) with the following variables: unmet need for contraception (IRR = 1.07), women's desire for children (5+ versus 0-2 children: IRR = 1.22), woman's number of siblings (8-20 versus 0-4: IRR = 1.03), and couples who desired different numbers of children (husband wants more: IRR = 1.04; husband wants fewer: IRR = 1.04). Low fertility in ever married/cohabitating women was associated with women's education (higher versus no education: IRR = 0.66), household wealth (highest versus lowest quintile: IRR = 0.93), and delayed sexual debut (25+ versus 8-18 years: IRR = 0.49). In never married women, low fertility was associated with education (higher versus no education: IRR = 0.22), household wealth (highest versus lowest quintile: IRR = 0.58), delayed sexual debut (25-49 versus 8-18 years: IRR = 0.43), and having an unmet need for contraception (IRR = 0.69). CONCLUSIONS: Although the study design does not allow causal conclusions, these results suggest several strategies to further reduce Rwanda's national fertility rate and support families to achieve their desired fertility. Strategies include policies and programs that promote delayed sexual debut via educational and economic opportunities for women, improved access to reproductive health information and services at schools and via health campaigns, and involvement of men in family planning decision making.