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Background: Routine Data Quality Assessments (RDQAs) were developed to measure and improve facility-level electronic medical record (EMR) data quality. We assessed if RDQAs were associated with improvements in data quality in KenyaEMR, an HIV care and treatment EMR used at 341 facilities in Kenya. Methods: RDQAs assess data quality by comparing information recorded in paper records to KenyaEMR. RDQAs are conducted during a one-day site visit, where approximately 100 records are randomly selected and 24 data elements are reviewed to assess data completeness and concordance. Results are immediately provided to facility staff and action plans are developed for data quality improvement. For facilities that had received more than one RDQA (baseline and follow-up), we used generalized estimating equation models to determine if data completeness or concordance improved from the baseline to the follow-up RDQAs. Results: 27 facilities received two RDQAs and were included in the analysis, with 2369 and 2355 records reviewed from baseline and follow-up RDQAs, respectively. The frequency of missing data in KenyaEMR declined from the baseline (31% missing) to the follow-up (13% missing) RDQAs. After adjusting for facility characteristics, records from follow-up RDQAs had 0.43-times the risk (95% CI: 0.32–0.58) of having at least one missing value among nine required data elements compared to records from baseline RDQAs. Using a scale with one point awarded for each of 20 data elements with concordant values in paper records and KenyaEMR, we found that data concordance improved from baseline (11.9/20) to follow-up (13.6/20) RDQAs, with the mean concordance score increasing by 1.79 (95% CI: 0.25–3.33). Conclusions: This manuscript demonstrates that RDQAs can be implemented on a large scale and used to identify EMR data quality problems. RDQAs were associated with meaningful improvements in data quality and could be adapted for implementation in other settings. [ABSTRACT FROM AUTHOR]

This paper documents a positive relationship between maize productivity in western Kenya and women’s empowerment in agriculture, measured using indicators derived from the abbreviated version of the Women’s Empowerment in Agriculture Index. Applying a cross-sectional instrumental-variable regression method to a data set of 707 maize farm households from western Kenya, we find that women’s empowerment in agriculture significantly increases maize productivity. Although all indicators of women’s empowerment significantly increase productivity, there is no significant association between the women’s workload (amount of time spent working) and maize productivity. Furthermore, the results show heterogenous effects with respect to women’s empowerment on maize productivity for farm plots managed jointly by a male and female and plots managed individually by only a male or female. More specifically, the results suggest that female- and male-managed plots experience significant improvements in productivity when the women who tend them are empowered. These findings provide evidence that women’s empowerment contributes not only to reducing the gender gap in agricultural productivity, but also to improving, specifically, productivity from farms managed by women. Thus, rural development interventions in Kenya that aim to increase agricultural productivity—and, by extension, improve food security and reduce poverty—could achieve greater impact by integrating women’s empowerment into existing and future projects. [ABSTRACT FROM AUTHOR]

Context: Ambivalence in pregnancy intentions is well-documented in sub-Saharan African (SSA) settings and has been associated with inconsistent use of contraception, thereby exposing women using contraception to the possibility of unintended pregnancies. A better understanding of the potential role for client counseling interventions in enabling women to achieve their pregnancy intentions is essential for aiding program efforts to reduce unintended pregnancies. Objective: To measure ambivalence in pregnancy intentions longitudinally and determine its association with the quality of care received, controlling for demographic, socio-economic and contextual factors among a cohort of family planning (FP) clients in Kenya. Methods: This paper uses data drawn from a prospective cohort study of FP clients to investigate the relationship between the quality of care received during FP service delivery and the decisiveness of their pregnancy intentions over time. The study tests the hypothesis that higher quality of care enables women to be less ambivalent about their pregnancy intentions. Binary logistic regression with random effects and multinomial logistic regression were used to assess the predictive effect of the quality of care received by a woman on the decisiveness or ambivalence of her pregnancy intentions, and on any shifts in ambivalence over time, controlling for background characteristics. The study recruited 1,957 women aged 15–49 years attending twelve family planning clinics in four counties in Central Kenya; of these, 1,053 women were observed for four rounds of data collection over a period of 24 months and form the sample for analysis. Findings: A substantial proportion (43%) of women expressed ambivalence about their intentions to become pregnant at some point during the study period, while over half (57%) remained unequivocal throughout the study. Almost one third of women (31%) shifted from being unequivocal to ambivalent and 12% shifted from ambivalence to being unequivocal. Women experiencing higher quality of care have lower odds of ever expressing ambivalence and higher odds of remaining unequivocal over time, net of other factors. Quality of care was not associated with a shift in ambivalence over time. Conclusion: FP programs offering higher quality of care are likely to support women to be more decisive in their pregnancy intentions. Improving the quality of care can contribute to reduced ambivalence and consequently reduced likelihood of unintended pregnancy among contraceptive users. This study provides further evidence of the benefits gained through providing high quality services. Trial registration: ClinicalTrials.gov [ABSTRACT FROM AUTHOR]

Broken water pumps continue to impede efforts to deliver clean and economically-viable water to the global poor. The literature has demonstrated that customers’ health benefits and willingness to pay for clean water are best realized when clean water infrastructure performs extremely well (>99% uptime). In this paper, we used sensor data from 42 Afridev-brand handpumps observed for 14 months in western Kenya to demonstrate how sensors and supervised ensemble machine learning could be used to increase total fleet uptime from a best-practices baseline of about 70% to >99%. We accomplish this increase in uptime by forecasting pump failures and identifying existing failures very quickly. Comparing the costs of operating the pump per functional year over a lifetime of 10 years, we estimate that implementing this algorithm would save 7% on the levelized cost of water relative to a sensor-less scheduled maintenance program. Combined with a rigorous system for dispatching maintenance personnel, implementing this algorithm in a real-world program could significantly improve health outcomes and customers’ willingness to pay for water services. [ABSTRACT FROM AUTHOR]

Background: Improved understanding and quantification of social contact patterns that govern the transmission dynamics of respiratory viral infections has utility in the design of preventative and control measures such as vaccination and social distancing. The objective of this study was to quantify an age-specific matrix of contact rates for a predominantly rural low-income population that would support transmission dynamic modeling of respiratory viruses. Methods and Findings: From the population register of the Kilifi Health and Demographic Surveillance System, coastal Kenya, 150 individuals per age group (<1, 1–5, 6–15, 16–19, 20–49, 50 and above, in years) were selected by stratified random sampling and requested to complete a day long paper diary of physical contacts (e.g. touch or embrace). The sample was stratified by residence (rural-to-semiurban), month (August 2011 to January 2012, spanning seasonal changes in socio-cultural activities), and day of week. Usable diary responses were obtained from 568 individuals (∼50% of expected). The mean number of contacts per person per day was 17.7 (95% CI 16.7–18.7). Infants reported the lowest contact rates (mean 13.9, 95% CI 12.1–15.7), while primary school students (6–15 years) reported the highest (mean 20.1, 95% CI 18.0–22.2). Rates of contact were higher within groups of similar age (assortative), particularly within the primary school students and adults (20–49 years). Adults and older participants (>50 years) exhibited the highest inter-generational contacts. Rural contact rates were higher than semiurban (18.8 vs 15.6, p = 0.002), with rural primary school students having twice as many assortative contacts as their semiurban peers. Conclusions and Significance: This is the first age-specific contact matrix to be defined for tropical Sub-Saharan Africa and has utility in age-structured models to assess the potential impact of interventions for directly transmitted respiratory infections. [ABSTRACT FROM AUTHOR]

Background: In Kenya, access to early infant diagnosis and viral load monitoring services for HIV patients on ART is significantly hampered by sample transportation challenges and long turnaround times. Near patient care testing technologies have the potential to obviate such constraints. The Cepheid GeneXpert was launched in 2010 as a TB assay and in 2014 as a potential point of care HIV viral load assay. Whereas it is widely is used for TB in Kenya, its utility for HIV testing has not been evaluated. Objective: To investigate the performance and usability characteristics of the GeneXpert HIV-1 qualitative and quantitative assay. Methods: This was a cross sectional study among 911 HIV Exposed infants and 310 HIV positive adults. Existing machines used for routine TB diagnosis were used in this study. The diagnostic accuracy of the qualitative assay was assessed using Roche CAP/CTM while the quantitative assay was assessed using with Abbott m2000 as the reference assays respectively. Statistical analysis was done using Stata/MP Version 14 for Mac. Concordance values and misclassification were calculated at the clinical cutoff of 1000 cp/ml. Results: The sensitivity, specificity and accuracy of the GeneXpert HIV-1 qualitative assay were 99.23% (95% CI 97.24–99.90%), 98.91% (95% CI 97.76–99.55%) and 99.00% respectively. For the quantitative assay, they were 92.50% (95% CI 79.61–98.43%), 100.00% and 97.00% respectively. All 30 (100%) users reported that the GeneXpert machine was easy to use, workflow was simple and TB diagnosis was not negatively affected. In our hands, the median turn-around time for an individual qualitative and quantitative test was 90 minutes. A total of 58 (4.34%) errors and 28 (2.10%) invalid outcomes were experienced; 44 (3.29%) tests did not run to completion due to power outages. Conclusion: GeneXpert HIV-1 qualitative and quantitative assay is an accurate test for the diagnosis of HIV in infants and for viral load monitoring. At the point of care, the GeneXpert machine's simple work flow, ease of use and short test turnaround time present the potential to improve access to HIV testing and viral load monitoring. To integrate HIV diagnosis into the existing GeneXpert platforms for TB Diagnosis, there is need to scale up the infrastructure and to change the way work is done. [ABSTRACT FROM AUTHOR]