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Despite increasing cesarean rates in Africa, there remain extensive gaps in the standard provision of care after cesarean birth. We present recommendations for discharge instructions to be provided to women following cesarean delivery in Rwanda, particularly rural Rwanda, and with consideration of adaptable guidelines for sub-Saharan Africa, to support recovery during the postpartum period. These guidelines were developed by a Technical Advisory Group comprised of clinical, program, policy, and research experts with extensive knowledge of cesarean care in Africa. The final instructions delineate between normal and abnormal recovery symptoms and advise when to seek care. The instructions align with global postpartum care guidelines, with additional emphasis on care practices more common in the region and address barriers that women delivering via cesarean may encounter in Africa. The recommended timeline of postpartum visits and visit activities reflect the World Health Organization protocols and provide additional activities to support women who give birth via cesarean. These guidelines aim to standardize communication with women at the time of discharge after cesarean birth in Africa, with the goal of improved confidence and clinical outcomes among these individuals.

In rural Africa where access to medical personnel is limited, telemedicine can be leveraged to empower community health workers (CHWs) to support effective postpartum home-based care after cesarean section (c-section). As a first step toward telemedicine, we assessed the sensitivity, specificity, and interrater reliability of image-based diagnosis of surgical site infections (SSIs) among women delivering via c-section at a rural Rwandan Hospital.Women ≥18 years who underwent c-section from March to October 2017 at Kirehe District Hospital (KDH) were enrolled. On postoperative day 10 at KDH, participants underwent a physical examination by a general practitioner, who provided a diagnosis of SSI or no SSI. Trained CHWs photographed patients' incisions and the collected images were shown to six physicians, who upon review, assigned one of the following diagnoses to each image: definite SSI, suspected SSI, suspected no SSI, and definite no SSI, which were compared with the diagnoses based on physical exam. We report the sensitivity and specificity and assessed reviewer agreement using Gwet's AC1.569 images were included, with 61 women (10.7%) diagnosed with an SSI. Of the 3414 image-reviews, 49 (1.4%) could not be assigned diagnoses due to image quality. The median sensitivity and specificity were 0.83 and 0.69, respectively. The Gwet's AC1 estimate for binary classification was 0.46.We demonstrate decent accuracy but only moderate consistency for photograph-based SSI diagnosis. Strategies to improve overall agreement include providing clinical information to accompany photographs, providing a baseline photograph for comparison, and implementing photograph-taking processes aimed at improving image quality.

Community health worker (CHW) interventions have been utilized to address barriers that prevent pregnant women from delivering in health facilities in low- and middle-income countries (LMICs). The objective of this research was to assess the programmatic factors that increase the likelihood of health facility delivery within a large digital health-supported CHW program in Zanzibar, Tanzania.This study included 36,693 women who were enrolled in the Safer Deliveries program with a live birth between January 1, 2017 and July 31, 2019. We assessed whether long-term enrollment, recency of CHW pregnancy visit prior to delivery, and number of routine home pregnancy visits were associated with an increased likelihood of health facility delivery compared to home delivery. We used Chi-squared tests to assess bivariate relationships and performed logistic regression analyses to assess the association between each programmatic variable and health facility delivery, adjusting for relevant confounders.We found that long-term enrollment was significantly associated with increased likelihood of health facility delivery, with the strongest relationship among women with a previous home delivery (OR = 1.4, 95%CI [1.0,1.7]). Among first-time mothers, two or more pregnancy visits by a CHW was positively associated with health facility delivery (OR = 1.8, 95%CI [1.2, 2.7]). Recent pregnancy visit by a CHW was positively associated with health facility delivery, but was not significant at the α = 0.05 level.In this program, we found evidence that at least two routine home pregnancy visits, longer length of enrollment in the program, and recency of home visit to the delivery date were strategies to increase health facility delivery rates among enrolled mothers. Maternal and child health programs should undertake similar evaluations to improve program delivery.

To examine changes in vaccination of children younger than 1 year during the coronavirus disease 2019 (COVID-19) pandemic (March 2020-August 2021) in Haiti, Lesotho, Liberia and Malawi.We used data from health management information systems on vaccination of children aged 12 months or younger in districts supported by Partners In Health. We used data from January 2016 to February 2020 and a linear model with negative binomial distribution to estimate the expected immunization counts for March 2020-August 2021 with 95% prediction intervals, assuming no pandemic. We compared these expected levels with observed values and estimated the immunization deficits or excesses during the pandemic months.Baseline vaccination counts varied substantially by country, with Lesotho having the lowest count and Haiti the highest. We observed declines in vaccination administration early in the COVID-19 pandemic in Haiti, Lesotho and Liberia. Continued declines largely corresponded to high rates of COVID-19 infection and discrete stock-outs. By August 2021, vaccination levels had returned to close to or above expected levels in Haiti, Liberia and Lesotho; in Malawi levels remained below expected.Patterns of childhood immunization coverage varied by country over the course of the pandemic, with significantly lower than expected vaccination levels seen in one country during subsequent COVID-19 waves. Governments and health-care stakeholders should monitor vaccine coverage closely and consider interventions, such as community outreach, to avoid or combat the disruptions in childhood vaccination.Étudier les changements en matière de vaccination des enfants âgés de moins d’un an durant la pandémie de maladie à coronavirus 2019 (COVID-19) en Haïti, au Lesotho, au Liberia et au Malawi, entre mars 2020 et août 2021.Nous avons utilisé les données issues des systèmes d'information pour la gestion de la santé et portant sur la vaccination des enfants de moins de 12 mois, dans les districts soutenus par l'association Partners In Health. Nous nous sommes appuyés sur des données collectées entre janvier 2016 et février 2020, ainsi que sur un modèle linéaire avec distribution binomiale négative, afin d'estimer les chiffres d'immunisation attendus pour la période allant de mars 2020 à août 2021 en appliquant des intervalles de prévision de 95%, en supposant qu'il n'y ait pas eu de pandémie. Enfin, nous avons comparé ces prévisions avec les valeurs observées, puis calculé les excédents ou déficits en la matière pendant les mois de pandémie.Les chiffres de vaccination initiaux étaient très différents d'un pays à l'autre, le Lesotho enregistrant le plus faible taux et Haïti, le plus élevé. Nous avons constaté une diminution de l'administration des vaccins au début de la pandémie de COVID-19 en Haïti, au Lesotho et au Liberia. Les baisses continues correspondaient à des niveaux élevés d'infection à la COVID-19 et à des ruptures de stock distinctes. En août 2021, les taux de vaccination avaient repris un cours normal ou supérieur à la norme en Haïti, au Liberia et au Lesotho; au Malawi, ils sont restés inférieurs aux résultats escomptés.Les schémas de couverture vaccinale infantile ont varié en fonction des pays tout au long de la pandémie, avec des taux de vaccination nettement inférieurs aux prévisions dans l'un des pays durant les vagues successives de COVID-19. Les gouvernements et acteurs du secteur de la santé devraient surveiller attentivement la couverture vaccinale et envisager des interventions telles que la sensibilisation communautaire s'ils souhaitent éviter ou mettre fin aux interruptions dans la vaccination des enfants.Analizar los cambios en la vacunación de los niños menores de 1 año durante la pandemia de la coronavirosis de 2019 (COVID-19) (entre marzo de 2020 y agosto de 2021) en Haití, Lesotho, Liberia y Malawi.Se emplearon datos de los sistemas de información de gestión sanitaria sobre la vacunación de niños de 12 meses o menos en los distritos que reciben apoyo de Partners In Health. Se usaron datos de enero de 2016 a febrero de 2020 y un modelo lineal con distribución binomial negativa para estimar las cifras de inmunización esperadas para el periodo de marzo de 2020 a agosto de 2021 con intervalos de predicción del 95 %, suponiendo que no hay pandemia. Se compararon estos niveles esperados con los valores observados y se estimaron los déficits o excesos de inmunización durante los meses de la pandemia.El número de vacunas de referencia varió bastante según el país, siendo Lesotho el que tuvo el número más bajo y Haití el más alto. Se observó una disminución en la administración de vacunas al principio de la pandemia de la COVID-19 en Haití, Lesotho y Liberia. Las disminuciones continuas fueron en gran medida consecuencia de las altas tasas de infección por la COVID-19 y a la escasez de existencias. En agosto de 2021, los niveles de vacunación se habían acercado o superado los niveles esperados en Haití, Liberia y Lesotho; en Malawi los niveles seguían siendo inferiores a los esperados.Los patrones de cobertura de la inmunización infantil variaron según el país en el transcurso de la pandemia, con niveles de vacunación mucho más bajos de lo esperado en un país durante las siguientes oleadas de la COVID-19. Los gobiernos y las partes interesadas en la atención sanitaria deben supervisar de cerca la cobertura de la vacunación y contemplar intervenciones, como la divulgación en la comunidad, para evitar o superar las interrupciones de la vacunación infantil.فحص التغييرات في تطعيم الأطفال الذين تقل أعمارهم عن سنة واحدة خلال جائحة مرض فيروس كورونا 2019 (كوفيد 19) (مارس/آذار 2020 إلى أغسطس/آب 2021) في هايتي وليسوتو وليبيريا وملاوي.قمنا باستخدام بيانات من أنظمة معلومات الإدارة الصحية بخصوص تطعيم الأطفال الذين تصل أعمارهم إلى 12 شهرًا أو أقل في المناطق التي يدعمها شركاء في الصحة. استخدمنا البيانات من يناير (كانون الثاني) 2016 إلى فبراير (شباط) 2020، ونموذج خطي بتوزيع سالب ذي الحدين لتقدير أعداد التحصين المتوقعة للفترة من مارس (آذار) 2020 إلى أغسطس (آب) 2021، مع فواصل توقع بنسبة 95%، بافتراض عدم وجود جائحة. قمنا بمقارنة هذه المستويات المتوقعة بالقيم التي تمت ملاحظتها، وقمنا بتقدير أوجه القصور أو التجاوزات في التحصين خلال أشهر الجائحة.اختلفت أعداد التلقيح الأساسية بشكل كبير حسب الدولة، حيث سجلت ليسوتو أقل عدد، بينما سجلت هايتي الأعلى. ولاحظنا انخفاضات في إدارة التطعيم في وقت مبكر من جائحة كوفيد 19 في هايتي وليسوتو وليبيريا. وتتماشى الانخفاضات المستمرة إلى حد كبير مع المعدلات المرتفعة للإصابة بكوفيد 19، وحالات نفاد المخزون المستقلة. بحلول أغسطس (آب) 2021، عادت مستويات التطعيم إلى ما يقرب من المستويات المتوقعة أو أعلى منها في هايتي وليبيريا وليسوتو؛ بينما ظلت المستويات في ملاوي أقل من المتوقع.اختلفت أنماط تغطية تحصين الأطفال حسب الدولة خلال فترة الجائحة، مع مستويات تطعيم أقل من المتوقع بشكل ملحوظ في دولة واحدة خلال موجات كوفيد 19 التالية. يجب على الحكومات وأصحاب المصلحة في الرعاية الصحية القيام بمراقبة تغطية اللقاح عن كثب والنظر في التدخلات، مثل التوعية المجتمعية، لتجنب أو مكافحة الاضطرابات في تطعيم الأطفال.调查海地、莱索托、利比里亚、和马拉维在新型冠状病毒肺炎 (COVID-19) 疫情期间（2020 年 3 月至 2021 年 8 月）1 岁以下的儿童疫苗接种的变化情况。.我们使用了健康管理信息系统提供的由健康合作伙伴支持的地区 12 个月及以下儿童接种疫苗的数据。我们使用 2016 年 1 月至 2020 年 2 月的数据和负二项分布的线性模型，来估计 2020 年 3 月至 2021 年 8 月的疫苗接种剂数，假设没有疫情，预测区间为 95%。我们将这些预期水平与观察值进行了比较，并估计了疫情期间的免疫缺陷或免疫反应过度情况。.不同国家的基线疫苗接种计数差别很大，莱索托的疫苗接种计数最低，海地最高。我们观察到海地、莱索托和利比里亚在新型冠状病毒肺炎疫情早期疫苗接种率下降。这种持续下降在很大程度上与新型冠状病毒肺炎感染率高和离散性缺货有关。到 2021 年 8 月，海地、莱索托和利比里亚的疫苗接种水平已恢复到接近或高于预期水平；马拉维的接种水平仍低于预期水平。.在疫情期间，各国的儿童免疫接种覆盖模式各不相同，在随后新型冠状病毒肺炎的反复爆发中，一个国家的疫苗接种水平明显低于预期水平。政府和医疗卫生利益相关者应密切监测疫苗接种覆盖率，并考虑采取干预措施，如社区外联，以避免或应对儿童疫苗接种中断的问题。.Изучить изменения в вакцинации детей младше 1 года во время пандемии коронавирусной инфекции 2019 года (COVID-19) (март 2020 г. — август 2021 г.) в Гаити, Лесото, Либерии и Малави.Авторы использовали данные из информационных систем управления в области здравоохранения о вакцинации детей в возрасте 12 месяцев и младше в районах, которые получают поддержку от организации «Партнеры во имя здоровья». Авторы использовали данные с января 2016 г. по февраль 2020 г., а также линейную модель с отрицательным биномиальным распределением для оценки ожидаемого числа иммунизаций на март 2020 г. — август 2021 г. с 95%-ми интервалами прогнозирования при условии отсутствия пандемии. Авторы сравнили эти ожидаемые уровни с наблюдаемыми значениями и оценили дефицит или избыток иммунизации в месяцы пандемии.Исходные показатели вакцинации существенно различались в разных странах: самый низкий показатель был в Лесото, а самый высокий — в Гаити. В начале пандемии COVID-19 наблюдалось снижение уровня вакцинации в Гаити, Лесото и Либерии. Продолжающееся снижение в значительной степени соответствовало высоким показателям заражения COVID-19 и дискретным дефицитам. К августу 2021 г. в Гаити, Либерии и Лесото уровни вакцинации вернулись к ожидаемым уровням или превысили их. В Малави уровни остались ниже ожидаемых.На протяжении пандемии характер охвата детей иммунизацией отличался в разных странах, при этом в одной стране во время последующих волн COVID-19 уровень вакцинации был значительно ниже, чем ожидалось. Правительствам и заинтересованным сторонам в сфере здравоохранения следует внимательно следить за охватом вакцинацией и предусматривать информационно-просветительскую работу с населением во избежание сбоев в вакцинации детей или для противостояния таким сбоям.

Access to hepatitis C (HCV) testing and treatment is still limited globally. To address this, the Government of Rwanda launched a voluntary mass screening and treatment campaign in 2017. We studied the progression of patients through the cascade of HCV care during this campaign. We conducted a retrospective cohort study and included all patients screened at 46 hospitals between April 2017 and October 2019. We used hierarchical logistic regression to assess factors associated with HCV positivity, gaps in care, and treatment failure. A total of 860,801 people attended the mass screening during the study period. Some 5.7% tested positive for anti-HCV, and 2.9% were confirmed positive. Of those who were confirmed positive, 52% initiated treatment, and 72% of those initiated treatment, completed treatment and returned for assessment 12 weeks afterward. The cure rate was 88%. HCV positivity was associated with age, socio-economic status, sex, marital status, and HIV coinfection. Treatment failure was associated with cirrhosis, baseline viral load, and a family history of HCV. Our results suggest that future HCV screening and testing interventions in Rwanda and other similar settings should target high-risk groups. High dropout rates suggest that more effort should be put into patient follow-up to increase adherence to care.

Background Location and type of clinic where pediatric latent TB infection (LTBI) care is provided are associated with treatment completion and retention in care. Prior research has not evaluated joint clinical management occurring between care settings. Understanding care transfer dynamics and accessibility of clinics can inform pediatric LTBI care service delivery. Methods We conducted a retrospective cohort study of LTBI in children 0-17 years old who were prescribed outpatient treatment in two Boston-area health systems from 2017-2019. We defined “initial clinical setting” (categorized as primary care or TB/infectious diseases clinic) as the location where the first LTBI medication was prescribed. Through chart review, we determined if care was transferred to a different (“final”) clinic setting during treatment. We calculated driving time between a child’s home address and initial and final treatment clinics. The primary outcome was frequency of care transfer after starting treatment. In a secondary analysis, we used two multivariable logistic regression models (adjusted for age, sex, and use of rifamycin-based treatment) to evaluate associations between completion and distance to and type of initial and final treatment clinic. Results We identified 142 children who started LTBI treatment as outpatients; 110 started treatment in primary care clinics and 32 in TB/infectious diseases clinics. Overall, 20/142 (14%) transferred TB care to a different clinic after starting treatment. A total of 101/142 (71%) patients completed treatment. Neither initial treatment location nor driving time to initial clinic were significantly associated with treatment completion (Table 1). However, final treatment in a TB clinic was associated with higher odds of treatment completion than final treatment in a primary care clinic (aOR 2.71 [95%CI 1.06-6.91], P=0.04); time to clinic was not associated with completion (Table 2). Figure 1.Patient transfers after starting LTBI treatment.Table 1.Initial treatment location: Univariable and multivariable analysis of factors associated with treatment completion.1Adjusted for time to clinic and location of initial treatment as well as age, sex, and use of rifamycin-based treatment.Table 2.Final treatment location: Univariable and multivariable analysis of factors associated with treatment completion.1Adjusted for time to clinic and location of final treatment as well as age, sex, and use of rifamycin-based treatment. Conclusion Among children with LTBI in a large metropolitan area, more patients received treatment in primary care clinics than in TB clinics. Care transfers were relatively uncommon after starting treatment. A TB clinic as a final treatment location was associated with increased odds of treatment completion. Disclosures Jessica Haberer, MD, MS, Merck: Advisor/Consultant|Natera: Stocks/Bonds.

US guidelines recommend interferon gamma release assays (IGRAs) for diagnosis of tuberculosis infection in children. In this retrospective cohort study, IGRA use in children 2-17 years of age increased substantially between 2015 and 2021. Testing in inpatient/subspecialty settings (vs. primary care), public (vs. private) insurance, lower age and non-English preferred language were associated with increased odds of receiving an IGRA.

IntroductionIn sub-Saharan Africa, youth living with HIV, especially those who have lost one or both parents, face economic, socially and psychological challenges that hinder adherence to ART, ultimately leading to poor health outcomes. Partners In Health/Inshuti Mu Buzima implemented an Adolescent Support Group (ASG) to support HIV-positive youth aged 15–25 years. During the evaluation of the ASG program, we sought to better understand youths' lived experiences to improve our delivery of HIV care.MethodsWe conducted qualitative in-depth, semi-structured individual interviews with youth enrolled in the ASG program. All interviews were conducted in-person or by telephone. Thematic analysis applying the framework approach with parallel inductive coding in Kinyarwanda and English was used.ResultsWe interviewed 35 youth who ranged in age from 16 to 29 years. The main themes related to the lived experiences of youth were (a) Experiences living with HIV, including disclosure, stigma, interactions with the health care system, and medication adherence; (b) external challenges, defined as challenges that were not related to the implementation of the ASG program; and (c) personal vision. Almost all youth reported acquiring HIV from their mothers and disclosure of HIV status occurred around the age of 10. Disclosure was often unintentional and followed by internalized and enacted stigma. Many reported poor past medication adherence which improved following enhanced counselling. External challenges were overwhelmingly economic in nature, and orphanhood was a root cause of other challenges such as difficulty accessing education, lack of transport to health facility, and lack of insurance fees. Despite these challenges, youth have an optimistic view of the future with dreams of health, economic attainment, marriage, and children.ConclusionHealthcare providers should empower caregivers to support HIV disclosure. Supporting youth as they face many economic challenges could help address socio-economic barriers to good health and promote holistic well-being.

BackgroundMaternal and neonatal health outcomes in low- and middle-income countries (LMICs) have improved over the last two decades. However, many pregnant women still deliver at home, which increases the health risks for both the mother and the child. Community health worker programs have been broadly employed in LMICs to connect women to antenatal care and delivery locations. More recently, employment of digital tools in maternal health programs have resulted in better care delivery and served as a routine mode of data collection. Despite the availability of rich, patient-level data within these digital tools, there has been limited utilization of this type of data to inform program delivery in LMICs.MethodsWe use program data from 38,787 women enrolled in Safer Deliveries, a community health worker program in Zanzibar, to build a generalizable prediction model that accurately predicts whether a newly enrolled pregnant woman will deliver in a health facility. We use information collected during the enrollment visit, including demographic data, health characteristics and current pregnancy information. We apply four machine learning methods: logistic regression, LASSO regularized logistic regression, random forest and an artificial neural network; and three sampling techniques to address the imbalanced data: undersampling of facility deliveries, oversampling of home deliveries and addition of synthetic home deliveries using SMOTE.ResultsOur models correctly predicted the delivery location for 68%–77% of the women in the test set, with slightly higher accuracy when predicting facility delivery versus home delivery. A random forest model with a balanced training set created using undersampling of existing facility deliveries accurately identified 74.4% of women delivering at home.ConclusionsThis model can provide a “real-time” prediction of the delivery location for new maternal health program enrollees and may enable early provision of extra support for individuals at risk of not delivering in a health facility, which has potential to improve health outcomes for both mothers and their newborns. The framework presented here is applicable in other contexts and the selection of input features can easily be adapted to match data availability and other outcomes, both within and beyond maternal health.

In public health research, finite resources often require that decisions be made at the study design stage regarding which individuals to sample for detailed data collection. At the same time, when study units are naturally clustered, as patients are in clinics, it may be preferable to sample clusters rather than the study units, especially when the costs associated with travel between clusters are high. In this setting, aggregated data on the outcome and select covariates are sometimes routinely available through, for example, a country's Health Management Information System. If used wisely, this information can be used to guide decisions regarding which clusters to sample, and potentially obtain gains in efficiency over simple random sampling. In this article, we derive a series of formulas for optimal allocation of resources when a single-stage stratified cluster-based outcome-dependent sampling design is to be used and a marginal mean model is specified to answer the question of interest. Specifically, we consider two settings: (i) when a particular parameter in the mean model is of primary interest; and, (ii) when multiple parameters are of interest. We investigate the finite population performance of the optimal allocation framework through a comprehensive simulation study. Our results show that there are trade-offs that must be considered at the design stage: optimizing for one parameter yields efficiency gains over balanced and simple random sampling, while resulting in losses for the other parameters in the model. Optimizing for all parameters simultaneously yields smaller gains in efficiency, but mitigates the losses for the other parameters in the model.

Background We provided sexually transmitted infection (STI) screening and facilitated partner notification and treatment among women participating in a periconception HIV prevention program in southwestern Uganda to understand follow-up STI incidence. Methods Women at-risk for HIV exposure while planning for pregnancy completed laboratory screening for chlamydia, gonorrhea, trichomoniasis, and syphilis at enrollment and 6 months of follow-up and/or incident pregnancy; facilitated partner notification and treatment were offered for those with positive tests. We performed a logistic regression to determine correlates of follow-up STI. Results Ninety-four participants completed enrollment STI screening with a median age of 29 (IQR 26–34); 23 (24%) had ≥1 STI. Of the 23 participants with enrollment STI(s), all completed treatment and 19 (83%) returned for follow-up; 18 (78%) reported delivering partner notification cards and discussing STIs with partner(s), and 14 (61%) reported all partners received STI treatment. Of the 81 (86%) who successfully completed follow-up STI screening, 17 (21%) had ≥1 STI. The STI incidence rate was 29.0 per 100 person-years. In univariable regression analysis, enrollment STI, younger age, less education, and alcohol consumption were all significantly associated with follow-up STI. Conclusions We demonstrated high enrollment and follow-up STI rates and moderate participant-reported partner treatment among women planning for pregnancy in Uganda despite partner notification and treatment. Novel STI partner notification and treatment interventions are needed to decrease the STI burden, especially among women planning for and with pregnancy.

Background Caesarean sections account for roughly one third of all surgical procedures performed in low-income countries. Due to lack of standardised post-discharge follow-up protocols and practices, most of available data are extracted from clinical charts during hospitalization and are thus sub-optimal for answering post-discharge outcomes questions. This study aims to determine enablers and barriers to returning to the hospital after discharge among women who have undergone a c-section at a rural district hospital in Rwanda. Methods Women aged ≥ 18 years who underwent c-section at Kirehe District Hospital in rural Rwanda in the period March to October 2017 were prospectively followed. A structured questionnaire was administered to participants and clinical data were extracted from medical files between March and October 2017. At discharge, consenting women were given an appointment to return for follow-up on postoperative day 10 (POD 10) (± 3 days) and provided a voucher to cover transport and compensation for participation to be redeemed on their return. Study participants received a reminder call on the eve of their scheduled appointment. We used a backward stepwise logistic regression, at an α = 0.05 significance level, to identify enablers and barriers associated with post-discharge follow-up return. Results Of 586 study participants, the majority (62.6%) were between 21–30 years old and 86.4% had a phone contact number. Of those eligible, 90.4% returned for follow-up. The predictors of return were counselling by a female data collector (OR = 9.85, 95%CI:1.43–37.59) and receiving a reminder call (OR = 16.47, 95%CI:7.07–38.38). Having no insurance reduced the odds of returning to follow-up (OR = 0.03, 95%CI:0.03–0.23), and those who spent more than 10.6 Euro for transport to and from the hospital were less likely to return to follow-up (OR = 0.14, 95%CI:0.04- 0.50). Conclusion mHealh interventions using calls or notifications can increase the post-discharge follow-up uptake. The reminder calls to patients and discharge counselling by a gender-matching provider had a positive effect on return to care. Further interventions are needed targeting the uninsured and patients facing transportation hardship. Additionally, association between counselling of women patients by a female data collector and greater return to follow-up needs further exploration to optimize counselling procedures.

The global movement to use routine information for managing health systems to achieve the Sustainable Development Goals, relies on administrative data which have inherent biases when used to estimate coverage with health services. Health policies and interventions planned with incorrect information can have detrimental impacts on communities. Statistical inferences using administrative data can be improved when they are combined with random probability survey data. Sometimes, survey data are only available for some districts. We present new methods for extending combined estimation techniques to all districts by combining additional data sources. Our study uses data from a probability survey (n = 1786) conducted during 2015 in 19 of Benin’s 77 communes and administrative count data from all of them for a national immunization day (n = 2,792,803). Communes are equivalent to districts. We extend combined-data estimation from 19 to 77 communes by estimating denominators using the survey data and then building a statistical model using population estimates from different sources to estimate denominators in adjacent districts. By dividing administrative numerators by the model-estimated denominators we obtain extrapolated hybrid prevalence estimates. Framing the problem in the Bayesian paradigm guarantees estimated prevalence rates fall within the appropriate ranges and conveniently incorporates a sensitivity analysis. Our new methodology, estimated Benin’s polio vaccination rates for 77 communes. We leveraged probability survey data from 19 communes to formulate estimates for the 58 communes with administrative data alone; polio vaccination coverage estimates in the 58 communes decreased to ranges consistent with those from the probability surveys (87%, standard deviation = 0.09) and more credible than the administrative estimates. Combining probability survey and administrative data can be extended beyond the districts in which both are collected to estimate coverage in an entire catchment area. These more accurate results will better inform health policy-making and intervention planning to reduce waste and improve health in communities.

Introduction While it is recognized that there are costs associated with postoperative patient follow-up, risk assessments of catastrophic health expenditures (CHEs) due to surgery in sub-Saharan Africa rarely include expenses after discharge. We describe patient-level costs for cesarean section (c-section) and follow-up care up to postoperative day (POD) 30 and evaluate the contribution of follow-up to CHEs in rural Rwanda. Methods We interviewed women who delivered via c-section at Kirehe District Hospital between September 2019 and February 2020. Expenditure details were captured on an adapted surgical indicator financial survey tool and extracted from the hospital billing system. CHE was defined as health expenditure of ≥ 10% of annual household expenditure. We report the cost of c-section up to 30 days after discharge, the rate of CHE among c-section patients stratified by in-hospital costs and post-discharge follow-up costs, and the main contributors to c-section follow-up costs. We performed a multivariate logistic regression using a backward stepwise process to determine independent predictors of CHE at POD30 at α ≤ 0.05. Results Of the 479 participants in this study, 90% were classified as impoverished before surgery and an additional 6.4% were impoverished by the c-section. The median out-of-pocket costs up to POD30 was US$122.16 (IQR: $102.94, $148.11); 63% of these expenditures were attributed to post-discharge expenses or lost opportunity costs (US$77.50; IQR: $67.70, $95.60). To afford c-section care, 64.4% borrowed money and 18.4% sold possessions. The CHE rate was 27% when only considering direct and indirect costs up to the time of discharge and 77% when including the reported expenses up to POD30. Transportation and lost household wages were the largest contributors to post-discharge costs. Further, CHE at POD30 was independently predicted by membership in community-based health insurance (aOR = 3.40, 95% CI: 1.21,9.60), being a farmer (aOR = 2.25, 95% CI:1.00,3.03), primary school education (aOR = 2.35, 95% CI:1.91,4.66), and small household sizes had 0.22 lower odds of experiencing CHE compared to large households (aOR = 0.78, 95% CI:0.66,0.91). Conclusion Costs associated with surgical follow-up are often neglected in financial risk calculations but contribute significantly to the risk of CHE in rural Rwanda. Insurance coverage for direct medical costs is insufficient to protect against CHE. Innovative follow-up solutions to reduce costs of patient transport and compensate for household lost wages need to be considered.

The neonatal mortality rate in Rwanda remains above the United Nations Sustainable Development Goal 3 target of 12 deaths per 1,000 live births. As part of a larger effort to reduce preventable neonatal deaths in the country, we conducted a study to examine risk factors for low birthweight. The data was collected via a cost-efficient cluster-based outcome-dependent sampling scheme wherein clusters of individuals (health centers) were selected on the basis of, in part, the outcome rate of the individuals. For a given dataset collected via a cluster-based outcome-dependent sampling scheme, estimation for a marginal model may proceed via inverse-probability-weighted generalized estimating equations, where the cluster-specific weights are the inverse probability of the health center's inclusion in the sample. In this paper, we provide a detailed treatment of the asymptotic properties of this estimator, together with an explicit expression for the asymptotic variance and a corresponding estimator. Furthermore, motivated by the study we conducted in Rwanda, we propose a number of small-sample bias corrections to both the point estimates and the standard error estimates. Through simulation, we show that applying these corrections when the number of clusters is small generally reduces the bias in the point estimates, and results in closer to nominal coverage. The proposed methods are applied to data from 18 health centers and 1 district hospital in Rwanda.

The utilization of community health worker (CHW) programmes to improve maternal and neonatal health outcomes has become widely applied in low- and middle-income countries. While current research has focused on discerning the effect of these interventions, documenting the process of implementing, scaling and sustaining these programmes has been largely ignored. Here, we focused on the implementation of the Safer Deliveries CHW programme in Zanzibar, a programme designed to address high rates of maternal and neonatal mortality by increasing rates of health facility delivery and postnatal care visits. The programme was implemented and brought to scale in 10 of 11 districts in Zanzibar over the course of 3 years by D-tree International and the Zanzibar Ministry of Health. As the programme utilized a mobile app to support CHWs during their visits, a rich data resource comprised of 133 481 pregnancy and postpartum home visits from 41 653 women and 436 CHWs was collected, enabling the evaluation of numerous measures related to intervention fidelity and health outcomes. Utilizing the framework of Steckler et al., we completed a formal process evaluation of the primary intervention, CHW home visits to women during their pregnancy and postpartum period. Our in-depth analysis and discussion will serve as a model for process evaluations of similar CHW programmes and will hopefully encourage future implementers to report analogous measures of programme performance.

Background: We aimed to develop and validate a screening algorithm to assist community health workers (CHWs) in identifying surgical site infections (SSIs) after cesarean section (c-section) in rural Africa. Methods: Patients were adult women who underwent c-section at a Rwandan rural district hospital between March and October 2017. A CHW administered a nine-item clinical questionnaire 10 ± 3 days post-operatively. Independently, a general practitioner (GP) administered the same questionnaire and assessed SSI presence by physical examination. The GP's SSI diagnosis was used as the gold standard. Using a simplified Classification and Regression Tree analysis, we identified a subset of screening questions with maximum sensitivity for the GP and CHW and evaluated the subset's sensitivity and specificity in a validation dataset. Then, we compared the subset's results when implemented in the community by CHWs with health center-reported SSI. Results: Of the 596 women enrolled, 525 (88.1%) completed the clinical questionnaire. The combination of questions concerning fever, pain, and discolored drainage maximized sensitivity for both the GPs (sensitivity = 96.8%; specificity = 85.6%) and CHWs (sensitivity = 87.1%; specificity = 73.8%). In the validation dataset, this subset had sensitivity of 95.2% and specificity of 83.3% for the GP-administered questions and sensitivity of 76.2% and specificity of 81.4% for the CHW-administered questions. In the community screening, the overall percent agreement between CHW and health center diagnoses was 81.1% (95% confidence interval: 77.2%–84.6%). Conclusions: We identified a subset of questions that had good predictive features for SSI, but its sensitivity was lower when administered by CHWs in a clinical setting, and it performed poorly in the community. Methods to improve diagnostic ability, including training or telemedicine, must be explored.

Background Since long travel times to reach health facilities are associated with worse outcomes, geographic accessibility is one of the six core global surgery indicators; this corresponds to the second of the “Three Delays Framework,” namely “delay in reaching a health facility.” Most attempts to estimate this indicator have been based on geographical information systems (GIS) algorithms. The aim of our study was to compare GIS derived estimates to self-reported travel times for patients traveling to a district hospital in rural Rwanda for emergency obstetric care. Methods Our study includes 664 women who traveled to undergo a Cesarean delivery in Kirehe, Rwanda. We compared self-reported travel time from home to the hospital (excluding waiting time) with GIS estimated travel times, which were computed using the World Health Organization tool AccessMod, using linear regression. Results The majority of patients used multiple modes of transportation (walking = 48.5%, public transport = 74.2%, private transport = 2.9%, and ambulance 70.6%). Self-reported times were longer than GIS estimates by a factor of 1.49 (95% CI 1.40–1.57). Concordance was higher when the GIS model took into account that all patients in Rwanda are referred via their health center (β = 1.12; 95% CI 1.05–1.18). Conclusions To our knowledge, in this largest to date GIS validation study for geographical access to healthcare in low- and middle-income countries, a standard GIS model was found to significantly underestimate real travel time, which likely is in part because it does not model the actual route patients are travelling. Therefore, previous studies of 2-h access to surgery will need to be interpreted with caution, and future studies should take local travelling conditions into account.

Background Many children in low- and middle-income countries fail to reach their cognitive potential, with experiences before age 3 critical in shaping long-term development. Zanzibar’s Jamii ni Afya program is the first national, digitally enabled community health volunteer (CHV) program promoting early childhood development (ECD) following the Nurturing Care Framework within an integrated maternal and child healthcare package. Using program baseline data, we explored home environment, caregivers’ parenting, health and nutrition knowledge and practices, and ECD outcomes in Zanzibar. Methods We conducted a national household survey among 499 children aged 18-29 months using two-stage cluster sampling in February 2019. The primary outcome was child development score measured using the Caregiver Reported Early Developmental Index (CREDI), with higher scores representing higher levels of child development. We analyzed CREDI scores, along with MICS questions on parenting knowledge, practices, and characteristics of the home environment. We developed multivariate regression models to assess associations between caregiver-child interactions, knowledge of dietary diversity, and ECD. Results Ten percent of children had overall CREDI z-scores 2 standard deviations [SD] or more below the global reference population mean, with 28% of children at risk of developmental delay with z-scores 1 SD or more below the mean. Cognitive and language domains were of highest concern (10.2 and 12.7% with z-score p = 0.002, 95%CI = [0.014, 0.058]), and dietary diversity knowledge (β = 0.564, p Conclusions Our findings demonstrate a positive association between both the frequency of caregiver child interactions and knowledge of adequate dietary diversity, and ECD outcomes. This aligns with global evidence that promoting early stimulation, play and learning opportunities, and dietary diversity can improve developmental outcomes. Further study is needed to establish causal relationships and assess the impact of ECD programming in Zanzibar.

To characterize losses from the pediatric tuberculosis (TB) infection care cascade to identify ways to improve TB infection care delivery.We conducted a retrospective cohort study of children (age18 years) screened for TB within 2 Boston-area health systems between January 2017 and May 2019. Patients who received a tuberculin skin test (TST) and/or an interferon gamma release assay (IGRA) were included.We included 13 353 tests among 11 622 patients; 93.9% of the tests were completed. Of 199 patients with positive tests for whom TB infection evaluation was clinically appropriate, 59.3% completed treatment or were recommended to not start treatment. Age 12-17 years (vs 5 years; aOR 1.59; 95% CI, 1.32-1.92), non-English/non-Spanish language preference (vs English; aOR, 1.34; 95% CI, 1.02-1.76), and receipt of an IGRA (vs TST, aOR, 30.82; 95% CI, 21.92-43.34) were associated with increased odds of testing completion. Odds of testing completion decreased as census tract social vulnerability index quartile increased (ie, social vulnerability worsened; most vulnerable quartile vs least vulnerable quartile, aOR, 0.77; 95% CI, 0.60-0.99). Odds of completing treatment after starting treatment were higher in females (vs males; aOR, 2.35; 95% CI, 1.14-4.85) and were lower in patients starting treatment in a primary care clinic (vs TB/infectious diseases clinic; aOR, 0.44; 95% CI, 0.27-0.71).Among children with a high proportion of negative TB infection tests, completion of testing was high, but completion of evaluation and treatment was moderate. Transitions toward IGRA testing will improve testing completion; interventions addressing social determinants of health are important to improve treatment completion.

Background Lot Quality Assurance Sampling (LQAS), a tool used for monitoring health indicators in low resource settings resulting in “high” or “low” classifications, assumes that determination of the trait of interest is perfect. This is often not true for diagnostic tests, with imperfect sensitivity and specificity. Here, we develop Lot Quality Assurance Sampling for Imperfect Tests (LQAS-IMP) to address this issue and apply it to a COVID-19 serosurveillance study design in Haiti. Methods We first derive a modified procedure, LQAS-IMP, that accounts for the sensitivity and specificity of a diagnostic test to yield correct classification errors. We then apply the novel LQAS-IMP to design an LQAS system to classify prevalence of SARS-CoV-2 antibodies among healthcare workers at eleven Zanmia Lasante health facilities in Haiti. Finally, we show the performance of the LQAS-IMP procedure in a simulation study. Results We found that when an imperfect diagnostic test is used, the classification errors in the standard LQAS procedure are larger than specified. In the modified LQAS-IMP procedure, classification errors are consistent with the specified maximum classification error. We then utilized the LQAS-IMP procedure to define valid systems for sampling at eleven hospitals in Haiti. Conclusion The LQAS-IMP procedure accounts for imperfect sensitivity and specificity in system design; if the accuracy of a test is known, the use of LQAS-IMP extends LQAS to applications for indicators that are based on laboratory tests, such as SARS-CoV-2 antibodies.

One of the greatest concerns in post-operative care is the infection of the surgical wound. Such infections are a particular concern in global health and low-resource areas, where microbial antibiotic resistance is often common. In order to help address this problem, there is a great interest in developing simple tools for early detection of surgical wounds. Motivated by this need, we describe the development of two Convolutional Neural Net (CNN) models designed to detect an infection in a surgical wound using a color image taken from a mobile device. These models were developed using image data collected from a clinical study with 572 women in Rural Rwanda, who underwent Cesarean section surgery and had photos taken approximately 10 days after surgery. Infected wounds (N=62) were diagnosed by a trained doctor through a physical exam. In our model development, we observed a trade-off between AUC accuracy and sensitivity, and we chose to optimize for sensitivity, to match its use as a screening tool. Our naïve CNN model, with a limited number of convolutions and parameters, achieved median AUC = 0.655, true positive rate sensitivity = 0.75, specificity = 0.58, classification accuracy = 0.86. The second CNN model, developed with transfer learning using the Resnet50 architecture, produced a median AUC = 0.639 sensitivity = 0.92, specificity = 0.18, and classification accuracy 0.82. We discuss the specific training and optimization methods used to compensate for significant class imbalance and maximize sensitivity.

The ability to detect surgical site infections (SSI) is a critical need for healthcare worldwide, but is especially important in low-income countries, where there is limited access to health facilities and trained clinical staff. In this paper, we present a new method of predicting SSI using a thermal image collected with a smart phone. Machine learning algorithms were developed using images collected as part of a clinical study that included 530 women in rural Rwanda who underwent cesarean section surgery. Thermal images were collected approximately 10 days after surgery, in conjunction with an examination by a trained doctor to determine the status of the wound (infected or not). Of the 530 women, 30 were found to have infected wounds. The data were used to develop two Convolutional Neural Net (CNN) models, with special care taken to avoid overfitting and address the problem of class imbalance in binary classification. The first model, a 6-layer naïve CNN model, demonstrated a median accuracy of AUC=0.84 with sensitivity=71% and specificity=87%. The transfer learning CNN model demonstrated a median accuracy of AUC=0.90 with sensitivity =95% and specificity=84%. To our knowledge, this is the first successful demonstration of a machine learning algorithm to predict surgical infection using thermal images alone.Clinical Relevance- This work establishes a promising new method for automated detection of surgical site infection.

Background The development of a surgical site infection (SSI) after cesarean section (c-section) is a significant cause of morbidity and mortality in low- and middle-income countries, including Rwanda. Rwanda relies on a robust community health worker (CHW)–led, home-based paradigm for delivering follow-up care for women after childbirth. However, this program does not currently include postoperative care for women after c-section, such as SSI screenings. Objective This trial assesses whether CHW’s use of a mobile health (mHealth)–facilitated checklist administered in person or via phone call improved rates of return to care among women who develop an SSI following c-section at a rural Rwandan district hospital. A secondary objective was to assess the feasibility of implementing the CHW-led mHealth intervention in this rural district. Methods A total of 1025 women aged ≥18 years who underwent a c-section between November 2017 and September 2018 at Kirehe District Hospital were randomized into the three following postoperative care arms: (1) home visit intervention (n=335, 32.7%), (2) phone call intervention (n=334, 32.6%), and (3) standard of care (n=356, 34.7%). A CHW-led, mHealth-supported SSI diagnostic protocol was delivered in the two intervention arms, while patients in the standard of care arm were instructed to adhere to routine health center follow-up. We assessed intervention completion in each intervention arm and used logistic regression to assess the odds of returning to care. Results The majority of women in Arm 1 (n=295, 88.1%) and Arm 2 (n=226, 67.7%) returned to care and were assessed for an SSI at their local health clinic. There were no significant differences in the rates of returning to clinic within 30 days (P=.21), with high rates found consistently across all three arms (Arm 1: 99.7%, Arm 2: 98.4%, and Arm 3: 99.7%, respectively). Conclusions Home-based post–c-section follow-up is feasible in rural Africa when performed by mHealth-supported CHWs. In this study, we found no difference in return to care rates between the intervention arms and standard of care. However, given our previous study findings describing the significant patient-incurred financial burden posed by traveling to a health center, we believe this intervention has the potential to reduce this burden by limiting patient travel to the health center when an SSI is ruled out at home. Further studies are needed (1) to determine the acceptability of this intervention by CHWs and patients as a new standard of care after c-section and (2) to assess whether an app supplementing the mHealth screening checklist with image-based machine learning could improve CHW diagnostic accuracy. Trial Registration ClinicalTrials.gov NCT03311399; https://clinicaltrials.gov/ct2/show/NCT03311399

BACKGROUND The development of a surgical site infection (SSI) after cesarean section (c-section) is a significant cause of morbidity and mortality in low- and middle-income countries, including Rwanda. Rwanda relies on a robust community health worker (CHW)–led, home-based paradigm for delivering follow-up care for women after childbirth. However, this program does not currently include postoperative care for women after c-section, such as SSI screenings. OBJECTIVE This trial assesses whether CHW’s use of a mobile health (mHealth)–facilitated checklist administered in person or via phone call improved rates of return to care among women who develop an SSI following c-section at a rural Rwandan district hospital. A secondary objective was to assess the feasibility of implementing the CHW-led mHealth intervention in this rural district. METHODS A total of 1025 women aged ≥18 years who underwent a c-section between November 2017 and September 2018 at Kirehe District Hospital were randomized into the three following postoperative care arms: (1) home visit intervention (n=335, 32.7%), (2) phone call intervention (n=334, 32.6%), and (3) standard of care (n=356, 34.7%). A CHW-led, mHealth-supported SSI diagnostic protocol was delivered in the two intervention arms, while patients in the standard of care arm were instructed to adhere to routine health center follow-up. We assessed intervention completion in each intervention arm and used logistic regression to assess the odds of returning to care. RESULTS The majority of women in Arm 1 (n=295, 88.1%) and Arm 2 (n=226, 67.7%) returned to care and were assessed for an SSI at their local health clinic. There were no significant differences in the rates of returning to clinic within 30 days (P=.21), with high rates found consistently across all three arms (Arm 1: 99.7%, Arm 2: 98.4%, and Arm 3: 99.7%, respectively). CONCLUSIONS Home-based post–c-section follow-up is feasible in rural Africa when performed by mHealth-supported CHWs. In this study, we found no difference in return to care rates between the intervention arms and standard of care. However, given our previous study findings describing the significant patient-incurred financial burden posed by traveling to a health center, we believe this intervention has the potential to reduce this burden by limiting patient travel to the health center when an SSI is ruled out at home. Further studies are needed (1) to determine the acceptability of this intervention by CHWs and patients as a new standard of care after c-section and (2) to assess whether an app supplementing the mHealth screening checklist with image-based machine learning could improve CHW diagnostic accuracy. CLINICALTRIAL ClinicalTrials.gov NCT03311399; https://clinicaltrials.gov/ct2/show/NCT03311399

Background Traditional medicine is commonly used in low- and middle-income countries (LMICs). Little is known about the use of traditional medicine among women undergoing cesarean section (c-section) and the association to surgical site infections (SSIs) in LMICs. In this study, we describe peripartum use of traditional medicines and the risk of SSIs among women delivering via c-section in rural Rwanda.Methods This prospective cohort study enrolled women who underwent c-section at Kirehe District Hospital in rural Rwanda between September 2019 and February 2020. We collected self-reported data regarding traditional medicine use before and during pregnancy and after discharge up to postoperative day (POD) 11. On POD 11 (+/- 3 days), the women returned to the hospital for a study follow-up visit. We used Fisher’s exact test to assess the relationship between sociodemographic characteristics and traditional medicine use, and logistic regression to determine the association between traditional medicine use and SSI development while controlling for confounders. Results Of the 841 women enrolled in this study, 45 (5.4%) reported using traditional medicine to get pregnant. Nearly 39% used traditional medicine during pregnancy; the majority (96.9%) for a pregnancy-related reason. Only four women (0.5%) reported traditional medicine use between c-section and the POD 11 study visit. Of the 775 women who responded at all time-points, 341 (44.0%) reported using traditional medicine at some point during pregnancy or c-section recovery. No demographic characteristics were significantly associated with traditional medicine use (p>0.05), except for smoking (p=0.048) and alcohol consumption (p=0.010). Both traditional medicine use during pregnancy (p=0.04, aOR=2.0, 95% CI: 1.05, 3.85) and at any time point (p=0.04, aOR=2.0, 95% CI: 1.04, 3.83) were associated with development of SSI.Conclusions Traditional medicine use among c-section patients was high in the peripartum period, particularly during pregnancy, and was significantly associated with SSI. Knowing patterns of traditional medicine use during the peripartum period can help providers collaborate with traditional healers and give appropriate, culturally-sensitive pregnancy and postoperative care and counseling to patients.

Some people with HIV (PWH) test positive multiple times without initiating antiretroviral therapy (ART). We surveyed 496 ART-eligible PWH following routine HIV testing at three clinics in Soweto and Gugulethu, South Africa in 2014-2015. Among repeat positive testers (RPTs) in this cohort, we compared rates of treatment initiation by prior treatment eligibility and assessed psychosocial predictors of treatment initiation in logistic regression models. RPTs represented 33.8% of PWH in this cohort. Less than half of those who reported eligibility for ART on prior testing started treatment upon retesting, in contrast to two thirds of RPTs who were previously ineligible for treatment who started treatment once they learned of their eligibility. Those who reported coping through substance use were more likely to decline treatment versus those not using substances. PWH who test repeatedly represent a vulnerable population at risk for ART non-initiation who may benefit from interventions addressing individualized coping strategies.

Introduction: While it is recognized that there are costs associated with postoperative patient follow-up, risk assessments of catastrophic health expenditures (CHEs) due to surgery in sub-Saharan Africa rarely include expenses after discharge. We describe patient-level costs for cesarean section (c-section) and follow-up care up to postoperative day (POD) 30 and evaluate the contribution of follow-up to CHEs in rural Rwanda.Methods: We interviewed women who delivered via c-section at Kirehe District Hospital between September 2019 and February 2020. Expenditure details were captured on an adapted surgical indicator financial survey tool and extracted from the hospital billing system. CHE was defined as health expenditure of ≥ 10% of annual household expenditure. We report the cost of c-section up to 30 days after discharge, the rate of CHE among c-section patients stratified by in-hospital costs and post-discharge follow-up costs, and the main contributors to c-section follow-up costs. Results: Of the 479 participants in this study, 90% were classified as impoverished before surgery and an additional 6.4% were impoverished by the c-section. The median out-of-pocket costs up to POD30 was US$122.16 (IQR: $102.94, $148.11); 63% of these expenditures were attributed to post-discharge expenses or lost opportunity costs (US$77.50; IQR: $67.70, $95.60). To afford c-section care, 64.4% borrowed money and 18.4% sold possessions. The CHE rate was 27% when only considering direct and indirect costs up to the time of discharge and 77% when including the reported expenses up to POD30. Transportation and lost household wages were the largest contributors to post-discharge costs. Conclusion: Costs associated with surgical follow-up are often neglected in financial risk calculations but contribute significantly to the risk of CHE in rural Rwanda. Insurance coverage for direct medical costs is insufficient to protect against CHE. Innovative follow-up solutions to reduce costs of patient transport and compensate for household lost wages need to be considered.

Background Women who deliver via cesarean section (c-section) experience short- and long-term complications that may affect their physical health and their ability to function normally. While physical health outcomes are routinely assessed and monitored, postpartum functional outcomes are not well understood from a patient’s perspective or characterized by clinicians. In Rwanda, 11% of rural women deliver via c-section. This study explores the functional recovery of rural Rwandan women after c-section and assesses factors that predict poor functionality at postoperative day (POD) 30. Methods Data were collected prospectively on POD 3, 11, and 30 from women delivering at Kirehe District Hospital between October 2019 and March 2020. Functionality was measured by self-reported overall health, energy level, mobility, self-care ability, and ability to perform usual activities. We computed composite mean scores with a maximum score of 4.0 and scores ≤ 2.0 reflected poor functionality. We assessed functionality with descriptive statistics and logistic regression. Results Of 617 patients, 54.0%, 25.9%, and 26.8% reported poor functional status at POD3, POD11, and POD30, respectively. At POD30, the most self-reported poor functionality dimensions were poor or very poor overall health (48.1%), and inability to perform usual activities (15.6%). In the adjusted model, women whose surgery lasted 30–45 minutes had higher odds of poor functionality (aOR = 1.85, p = 0.01), as did women who experienced intraoperative complications (aOR = 4.12, p = 0.037). High income patients had incrementally lower significant odds of poor functionality (aOR = 0.62 for every US$100 increase in monthly income, p = 0.04). Conclusion We found a high proportion of poor functionality 30 days post-c-section and while surgery lasting > 30 minutes and experiencing intra-operative complications was associated with poor functionality, a reported higher income status was associated with lower odds of poor functionality. Functional status assessments, monitoring and support should be included in post-partum care for women who delivered via c-section. Effective risk mitigating intervention should be implemented to recover functionality after c-section, particularly among low-income women and those undergoing longer surgical procedures or those with intraoperative complications.

The COVID-19 pandemic has heterogeneously affected use of basic health services worldwide, with disruptions in some countries beginning in the early stages of the emergency in March 2020. These disruptions have occurred on both the supply and demand sides of healthcare, and have often been related to resource shortages to provide care and lower patient turnout associated with mobility restrictions and fear of contracting COVID-19 at facilities. In this paper, we assess the impact of the COVID-19 pandemic on the use of maternal health services using a time series modelling approach developed to monitor health service use during the pandemic using routinely collected health information systems data. We focus on data from 37 non-governmental organisation-supported health facilities in Haiti, Lesotho, Liberia, Malawi, Mexico and Sierra Leone. Overall, our analyses indicate significant declines in first antenatal care visits in Haiti (18% drop) and Sierra Leone (32% drop) and facility-based deliveries in all countries except Malawi from March to December 2020. Different strategies were adopted to maintain continuity of maternal health services, including communication campaigns, continuity of community health worker services, human resource capacity building to ensure compliance with international and national guidelines for front-line health workers, adapting spaces for safe distancing and ensuring the availability of personal protective equipment. We employ a local lens, providing prepandemic context and reporting results and strategies by country, to highlight the importance of developing context-specific interventions to design effective mitigation strategies.

Background: As the volume of surgical cases in low- and middle-income countries (LMICs) increases, surgical-site infections (SSIs) are becoming more prevalent with anecdotal evidence of antimicrobial resistance (AMR), despite a paucity of data on resistance patterns. Objectives: As a primary objective, this prospective study aimed to describe the epidemiology of SSIs and the associated AMR among women who delivered by cesarean at a rural Rwandan hospital. As secondary objectives, this study also assessed patient demographics, pre- and post-operative antibiotic use, and SSI treatment. Methods: Women who underwent cesarean deliveries at Kirehe District Hospital between September 23rd, 2019, and March 16th, 2020, were enrolled prospectively. On postoperative day (POD) 11 (+/− 3 days), their wounds were examined. When an SSI was diagnosed, a wound swab was collected and sent to the Rwandan National Reference Laboratory for culturing and antibiotic susceptibility testing. Findings: Nine hundred thirty women were enrolled, of whom 795 (85.5%) returned for the POD 11 clinic visit. 45 (5.7%) of the 795 were diagnosed with SSI and swabs were collected from 44 of these 45 women. From these 44 swabs, 57 potential pathogens were isolated. The most prevalent bacteria were coagulase-negative staphylococci (n = 12/57, 20.3% of all isolates), and Acinetobacter baumannii complex (n = 9/57, 15.2%). 68.4% (n = 39) of isolates were gram negative; 86.7% if excluding coagulase-negative staphylococci. No gram-negative pathogens isolated were susceptible to ampicillin, and the vast majority demonstrated intermediate susceptibility or resistance to ceftriaxone (92.1%) and cefepime (84.6%). Conclusions: Bacterial isolates from SSI swab cultures in rural Rwanda predominantly consisted of gram-negative pathogens and were largely resistant to commonly used antibiotics. This raises concerns about the effectiveness of antibiotics currently used for surgical prophylaxis and treatment and may guide the appropriate selection of treatment of SSIs in rural Rwanda and comparable settings.

Background Cesarean sections (c-sections), the most common surgical procedures performed worldwide, are essential in reducing maternal and neonatal deaths. There is a paucity of research studies on c-section care and outcomes in rural African settings. The objective of this study was to describe demographic characteristics, clinical management, and maternal and neonatal outcomes among women receiving c-sections at Kirehe District Hospital (KDH) in rural Rwanda. Methods This retrospective cohort study included all women aged ≥ 18 y residing in KDH catchment area who delivered by c-section at KDH between April 1 and September 30, 2017. Demographic and clinical characteristics of these women and their newborns were collected using patient interviews and medical chart extraction. Descriptive analyses were performed, and frequency and percentages are reported. Results Of the 621 women included in the study, 45.7% (n = 284) were aged 25-34 y; 42.2% (n = 262) were married; 67.5% (n = 419) had primary education; and 75.7% (n = 470) were farmers by occupation. Burundian refugees living in the nearby Mahama Refugee Camp comprised 13.7% (n = 85) of the study population. The most common indication for c-section was having undergone a c-section previously (31.9%, n = 198), followed by acute fetal distress (30.8%, n = 191). Among those with previous c-section as the sole indication for surgery, 85.4% presented as either urgent or emergent cases. Postoperatively, 67.7% spent less than 4 d at the hospital and 96.1% had no postoperative complications before discharge. Approximately 10% (59/572) of neonates were admitted to the neonatal unit, with the most common reason being neonatal infection (59.6%, n = 31). Conclusions Our study found that previous delivery via c-section was the primary indication for c-section and that most of these cases were emergent or urgent on presentation. This study highlights the need for further research to explore the feasibility, safety, and appropriateness of vaginal birth after cesarean in rural district hospitals in sub-Saharan Africa.

Background Most maternal health programs in low- and middle- income countries estimate gestational age to provide appropriate antenatal care at the correct times throughout the pregnancy. Although various gestational dating methods have been validated in research studies, the performance of these methods has not been evaluated on a larger scale, such as within health systems. The objective of this research was to investigate the magnitude and impact of errors in estimated delivery dates on health facility delivery among women enrolled in a maternal health program in Zanzibar. Methods This study included 4225 women who were enrolled in the Safer Deliveries program and delivered before May 31, 2017. The exposure of interest was error in estimated delivery date categorized as: severe overestimate, when estimated delivery date (EDD) was 36 days or more after the actual delivery date (ADD); moderate overestimate, when EDD was 15 to 35 days after ADD; accurate, when EDD was 6 days before to 14 days after ADD; and underestimate, when EDD was 7 days or more before ADD. We used Chi-squared tests to identify factors associated with errors in estimated delivery dates. We performed logistic regression to assess the impact of errors in estimated delivery dates on health facility delivery adjusting for age, district of residence, HIV status, and occurrence of past home delivery. Results In our data, 28% of the estimated delivery dates were a severe overestimate, 23% moderate overestimate, 41% accurate, and 8% underestimate. Compared to women with an accurate delivery date, women with a moderate or severe overestimate were significantly less likely to deliver in a health facility (OR = 0.71, 95% CI: [0.59, 0.86]; OR = 0.74, 95% CI: [0.61, 0.91]). When adjusting for multiple confounders, women with moderate overestimates were significantly less likely to deliver in a health facility (AOR = 0.76, 95% CI: [0.61, 0.93]); the result moved slightly towards null for women with severe overestimates (AOR = 0.84, 95% CI: [0.69, 1.03]). Conclusions The overestimation of women’s EDDs reduces the likelihood of health facility delivery. To address this, maternal health programs should improve estimation of EDD or attempt to curb the effect of these errors within their programs.

Background Child growth stunting remains a challenge in sub-Saharan Africa, where 34% of children under 5 years are stunted, and causing detrimental impact at individual and societal levels. Identifying risk factors to stunting is key to developing proper interventions. This study aimed at identifying risk factors of stunting in Rwanda. Methods We used data from the Rwanda Demographic and Health Survey (DHS) 2014–2015. Association between children’s characteristics and stunting was assessed using logistic regression analysis. Results A total of 3594 under 5 years were included; where 51% of them were boys. The prevalence of stunting was 38% (95% CI: 35.92–39.52) for all children. In adjusted analysis, the following factors were significant: boys (OR 1.51; 95% CI 1.25–1.82), children ages 6–23 months (OR 4.91; 95% CI 3.16–7.62) and children ages 24–59 months (OR 6.34; 95% CI 4.07–9.89) compared to ages 0–6 months, low birth weight (OR 2.12; 95% CI 1.39–3.23), low maternal height (OR 3.27; 95% CI 1.89–5.64), primary education for mothers (OR 1.71; 95% CI 1.25–2.34), illiterate mothers (OR 2.00; 95% CI 1.37–2.92), history of not taking deworming medicine during pregnancy (OR 1.29; 95%CI 1.09–1.53), poorest households (OR 1.45; 95% CI 1.12–1.86; and OR 1.82; 95%CI 1.45–2.29 respectively). Conclusion Family-level factors are major drivers of children’s growth stunting in Rwanda. Interventions to improve the nutrition of pregnant and lactating women so as to prevent low birth weight babies, reduce poverty, promote girls’ education and intervene early in cases of malnutrition are needed.

Background Early detection of SARS-CoV-2 circulation is imperative to inform local public health response. However, it has been hindered by limited access to SARS-CoV-2 diagnostic tests and testing infrastructure. In regions with limited testing capacity, routinely collected health data might be leveraged to identify geographical locales experiencing higher than expected rates of COVID-19-associated symptoms for more specific testing activities. Methods We developed syndromic surveillance tools to analyse aggregated health facility data on COVID-19-related indicators in seven low- and middle-income countries (LMICs), including Liberia. We used time series models to estimate the expected monthly counts and 95% prediction intervals based on 4 years of previous data. Here, we detail and provide resources for our data preparation procedures, modelling approach and data visualisation tools with application to Liberia. Results To demonstrate the utility of these methods, we present syndromic surveillance results for acute respiratory infections (ARI) at health facilities in Liberia during the initial months of the COVID-19 pandemic (January through August 2020). For each month, we estimated the deviation between the expected and observed number of ARI cases for 325 health facilities and 15 counties to identify potential areas of SARS-CoV-2 circulation. Conclusions Syndromic surveillance can be used to monitor health facility catchment areas for spikes in specific symptoms which may indicate SARS-CoV-2 circulation. The developed methods coupled with the existing infrastructure for routine health data systems can be leveraged to monitor a variety of indicators and other infectious diseases with epidemic potential.

Background: Neonatal mortality continues to be a global challenge, particularly in low- and middle-income countries. There is growing work to reduce mortality through improving quality of systems and care, but less is known about sustainability of improvements in the setting post initial implementation. We conducted a 12-month sustainability assessment of All Babies Count (ABC), a district-wide quality improvement project including mentoring and improvement collaborative designed to improve quality and reduce neonatal mortality in two districts in rural Rwanda. Methods: We measured changes in key neonatal process, coverage, and outcome indicators between the completion of ABC implementation and 12 months after the completion. In addition, we conducted 4 focus group discussions and 15 individual in-depth interviews with health providers and facility and district leaders to understand factors that influenced sustainability of improvements. We used an inductive, content analytic approach to derive six themes related to the ABC sustainability to explain quantitative results. Findings: Twelve months after the completion of ABC implementation, we found continued improvements in core quality, coverage, and neonatal outcomes. During ABC, the percentage of women with 4 antenatal visits increased from 12% to 30% and remained stable 12 months post-ABC (30%, p = 0.7) with an increase in facility-based delivery from 92.6% at the end of ABC to 95.8% (p = 0.01) at 12-month post-ABC. During ABC intervention, the 2 districts decreased neonatal mortality from 30.1 to 19.4 deaths per 1,000 live births with maintenance of the lower mortality 12 months post-ABC (19.4 deaths per 1,000 live births, p = 0.7). Leadership buy-in and development of self-reliance encouraging internally generated solutions emerged as key factors to sustain improvements while staff turnover, famine, influx of refugees, and unintended consequences of new national newborn care policies threatened sustainability. Interpretation: Despite discontinuity of key ABC support, health facilities kept the momentum of good practices and were able to maintain or increase the level of prenatal, neonatal quality of care and outcomes over a period of 12 months following the end of initial ABC implementation. Additional studies are needed to determine the longer-term sustainability beyond one year.

Background Understanding the burden of common mental health disorders, such as depressive disorder, is the first step in strengthening prevention and treatment in humanitarian emergencies. However, simple random sampling methods may lead to a high risk of coercion in settings characterized by a lack of distinction between researchers and aid organizations, mistrust, privacy concerns, and the overarching power differential between researchers and populations affected by crises. This case analysis describes a sampling approach developed for a survey study of depressive disorder in a Syrian refugee camp in Greece (n = 135). Discussion Syrian refugees face an extraordinarily high burden of depressive disorder during the asylum process (43%), necessitating population screening, prevention, and treatment. In order to preserve the informed consent process in this refugee camp setting, the research team developed a two-phase sampling strategy using a map depicting the geographical layout of the housing units within the camp. In the first phase, camp management announced a research study was being undertaken and individuals were invited to volunteer to participate. The participants’ container (housing) numbers were recorded on the map, but were not linked to the survey data. Then, in the second phase, the camp map was used for complementary sampling to reach a sample sufficient for statistical analysis. As a result of the two phases of the sampling exercise, all eligible adults from half the containers in each block were recruited, producing a systematic, age- and sex-representative sample. Conclusions Combining sampling procedures in humanitarian emergencies can reduce the risk of coerced consent and bias by allowing participants to approach researchers in the first phase, with a second phase of sampling conducted to recruit a systematic sample. This case analysis illuminates the feasibility of a two-phase sampling approach for drawing a quasi-random, representative sample in a refugee camp setting.

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.

Introduction To combat poor clinical outcomes among HIV-positive youth, Partners In Health/Inshuti Mu Buzima (PIH/IMB) implemented Adolescent Support Groups (ASGs), which combined peer support and group-based economic incentives to promote treatment adherence, economic empowerment, and viral suppression. This study assesses the association between ASG membership and clinical outcomes among HIV-positive youth living in rural Rwanda. Methods We constructed a retrospective cohort using PIH/IMB’s electronic medical record (EMR) system. ASG members were matched to control youth within strata defined by health facility, year of birth, and whether the patient had enrolled in HIV services as a pediatric patient, as a PMTCT mother, or through another route. Our 12-month outcomes of interest were a) death-free retention in care, b) death-free retention with active follow-up, c) ≥80% adherence to appointment keeping, and d) viral load suppression ( Results Two-hundred sixty ASG members were identified in the EMR and matched to 209 control youth for analysis. After 12 months of follow-up, ASG members had similar outcomes to the control youth in terms of death-free retention (93% vs. 94%), death-free retention with active follow-up (79% vs. 78%), ≥80% adherence to appointment keeping (42% vs. 43%), and viral suppression (48% vs. 51%). We did not observe any significant associations between ASG participation and clinical outcomes in crude or adjusted models, nor did ASG members experience greater improvements than control youth in our difference-in-difference analysis. Conclusions The ASG program did not improve retention, appointment adherence, or viral suppression among HIV positive youth in rural Rwanda. Challenges implementing the intervention as designed underscore the importance of incorporating implementation strategies and youth perspectives in program design. This population remains vulnerable to poor clinical outcomes, and additional research is needed to better serve youth living with HIV.