Using Android and Open Data Kit Technology in Data Management for Research in Resource-Limited Settings in the Niger Delta Region of Nigeria: Cross-Sectional Household Survey

The microbiota-gut-brain-immune interface in the pathogenesis of neuroinflammatory diseases: a narrative review of the emerging literature

Importance

Research is beginning to elucidate the sophisticated mechanisms underlying the microbiota-gut-brain-immune interface, moving from primarily animal models to human studies. Findings support the dynamic relationships between the gut microbiota as an ecosystem (microbiome) within an ecosystem (host) and its intersection with the host immune and nervous systems. Adding this to the effects on epigenetic regulation of gene expression further complicates and strengthens the response. At the heart is inflammation, which manifests in a variety of pathologies including neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and Multiple Sclerosis (MS).

Observations

Generally, the research to date is limited and has focused on bacteria, likely due to the simplicity and cost-effectiveness of 16s rRNA sequencing, despite its lower resolution and inability to determine functional ability/alterations. However, this omits all other microbiota including fungi, viruses, and phages, which are emerging as key members of the human microbiome. Much of the research has been done in pre-clinical models and/or in small human studies in more developed parts of the world. The relationships observed are promising but cannot be considered reliable or generalizable at this time. Specifically, causal relationships cannot be determined currently. More research has been done in Alzheimer's disease, followed by Parkinson's disease, and then little in MS. The data for MS is encouraging despite this.

Conclusions and relevance

While the research is still nascent, the microbiota-gut-brain-immune interface may be a missing link, which has hampered our progress on understanding, let alone preventing, managing, or putting into remission neurodegenerative diseases. Relationships must first be established in humans, as animal models have been shown to poorly translate to complex human physiology and environments, especially when investigating the human gut microbiome and its relationships where animal models are often overly simplistic. Only then can robust research be conducted in humans and using mechanistic model systems.

Waiting Time and Patient Satisfaction in a Subspecialty Eye Hospital Using a Mobile Data Collection Kit: Pre-Post Quality Improvement Intervention

BACKGROUND

Waiting time can considerably increase the cost to both the clinic and the patient and be a major predictor of the satisfaction of eye care users. Efficient management of waiting time remains as a challenge in hospitals. Waiting time management will become even more crucial in the postpandemic era. A key consideration when improving waiting time is the involvement of eye care users. This study aimed at improving patient waiting time and satisfaction through the use of Plan-Do-Study-Act (PDSA) quality improvement cycles.

OBJECTIVE

The objectives of this study were to determine the waiting time and patient satisfaction, measure the association between waiting time and patient satisfaction, and determine the effectiveness of the PDSA model in improving waiting time and satisfaction.

METHODS

This was a pre-post quality improvement study among patients aged 19 to 80 years, who are consulting with the Magrabi International Council of Ophthalmology Cameroon Eye Institute. We used PDSA cycles to conduct improvement audits of waiting time and satisfaction over 6 weeks. A data collection app known as Open Data Kit (Get ODK Inc) was used for real-time tracking of waiting, service, and idling times at each service point. Participants were also asked whether they were satisfied with the waiting time at the point of exit. Data from 51% (25/49) preintervention participants and 49% (24/49) postintervention participants were analyzed using Stata 14 at .05 significance level. An unpaired 2-tailed t test was used to assess the statistical significance of the observed differences in times before and after the intervention. Logistic regression was used to examine the association between satisfaction and waiting time.

RESULTS

In total, 49 participants were recruited with mean age of 49 (SD 15.7) years. The preintervention mean waiting, service, and idling times were 450 (SD 96.6), 112 (SD 47), and 338 (SD 98.1) minutes, respectively. There was no significant association between patient waiting time and satisfaction (odds ratio 1, 95% CI 0.99-1; P=.37; χ23=0.4). The use of PDSA led to 15% (66 minutes/450 minutes) improvement in waiting time (t47=2; P=.05) and nonsignificant increase in patient satisfaction from 32% (8/25) to 33% (8/24; z=0.1; P=.92).

CONCLUSIONS

Use of PDSA led to a borderline statistically significant reduction of 66 minutes in waiting time over 6 weeks and an insignificant improvement in satisfaction, suggesting that quality improvement efforts at the clinic have to be made over a considerable period to be able to produce significant changes. The study provides a good basis for standardizing the cycle (consultation) time at the clinic. We recommend shortening the patient pathway and implementing other measures including a phasic appointment system, automated patient time monitoring, robust ticketing, patient pathway supervision, standard triaging, task shifting, physician consultation planning, patient education, and additional registration staff.

Tailoring Mobile Data Collection for Intervention Research in a Challenging Context: Development and Implementation in the Malakit Study

BACKGROUND

An interventional study named Malakit was implemented between April 2018 and March 2020 to address malaria in gold mining areas in French Guiana, in collaboration with Suriname and Brazil. This innovative intervention relied on the distribution of kits for self-diagnosis and self-treatment to gold miners after training by health mediators, referred to in the project as facilitators.

OBJECTIVE

This paper aims to describe the process by which the information system was designed, developed, and implemented to achieve the monitoring and evaluation of the Malakit intervention.

METHODS

The intervention was implemented in challenging conditions at five cross-border distribution sites, which imposed strong logistical constraints for the design of the information system: isolation in the Amazon rainforest, tropical climate, and lack of reliable electricity supply and internet connection. Additional constraints originated from the interaction of the multicultural players involved in the study. The Malakit information system was developed as a patchwork of existing open-source software, commercial services, and tools developed in-house. Facilitators collected data from participants using Android tablets with ODK (Open Data Kit) Collect. A custom R package and a dashboard web app were developed to retrieve, decrypt, aggregate, monitor, and clean data according to feedback from facilitators and supervision visits on the field.

RESULTS

Between April 2018 and March 2020, nine facilitators generated a total of 4863 form records, corresponding to an average of 202 records per month. Facilitators' feedback was essential for adapting and improving mobile data collection and monitoring. Few technical issues were reported. The median duration of data capture was 5 (IQR 3-7) minutes, suggesting that electronic data capture was not taking more time from participants, and it decreased over the course of the study as facilitators become more experienced. The quality of data collected by facilitators was satisfactory, with only 3.03% (147/4849) of form records requiring correction.

CONCLUSIONS

The development of the information system for the Malakit project was a source of innovation that mirrored the inventiveness of the intervention itself. Our experience confirms that even in a challenging environment, it is possible to produce good-quality data and evaluate a complex health intervention by carefully adapting tools to field constraints and health mediators' experience.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03695770; https://clinicaltrials.gov/ct2/show/NCT03695770.

MyCap: a flexible and configurable platform for mobilizing the participant voice

This paper provides a description of the MyCap data collection platform, utilization metrics, and vignettes associated with use from diverse research institutions. MyCap is a participant-facing mobile application for survey data collection and the automated administration of active tasks (activities performed by participants using mobile device sensors under semi-controlled conditions). Launched in 2018, MyCap is a no-code solution for research teams conducting longitudinal studies, integrates tightly with REDCap and is available at no cost to research teams at academic, nonprofit, or government organizations. MyCap has been deployed at multiple research institutions with application usage logged across 135 countries in 2021. Vignettes demonstrate that MyCap empowered research teams to explore and implement novel methods of information collection and use. MyCap’s integration with REDCap provides a comprehensive data collection ecosystem and is best suited for longitudinal studies with frequent requests for information from participants.

Simple clinical and laboratory predictors to improve empirical treatment strategies in areas of high scrub typhus and dengue endemicity, central Vietnam

Background

Dengue fever is highly endemic in Vietnam, but scrub typhus—although recognized as an endemic disease—remains underappreciated. These diseases together are likely to account for more than half of the acute undifferentiated fever burden in Vietnam. Scrub typhus (ST) is a bacterial disease requiring antimicrobial treatment, while dengue fever (DF) is of viral etiology and does not. The access to adequate diagnostics and the current understanding of empirical treatment strategies for both illnesses remain limited. In this study we aimed to contribute to the clinical decision process in the management of these two important etiologies of febrile illness in Vietnam.

Methods

Using retrospective data from 221 PCR-confirmed scrub typhus cases and 387 NS1 protein positive dengue fever patients admitted to five hospitals in Khanh Hoa province (central Vietnam), we defined predictive characteristics for both diseases that support simple clinical decision making with potential to inform decision algorithms in future. We developed models to discriminate scrub typhus from dengue fever using multivariable logistic regression (M-LR) and classification and regression trees (CART). Regression trees were developed for the entire data set initially and pruned, based on cross-validation. Regression models were developed in a training data set involving 60% of the total sample and validated in the complementary subsample. Probability cut points for the distinction between scrub typhus and dengue fever were chosen to maximise the sum of sensitivity and specificity.

Results

Using M-LR, following seven predictors were identified, that reliably differentiate ST from DF; eschar, regional lymphadenopathy, an occupation in nature, increased days of fever on admission, increased neutrophil count, decreased ratio of neutrophils/lymphocytes, and age over 40. Sensitivity and specificity of predictions based on these seven factors reached 93.7% and 99.5%, respectively. When excluding the “eschar” variable, the values dropped to 76.3% and 92.3%, respectively.

The CART model generated one further variable; increased days of fever on admission, when eschar was included, the sensitivity and specificity was 95% and 96.9%, respectively. The model without eschar involved the following six variables; regional lymphadenopathy, increased days of fever on admission, increased neutrophil count, increased lymphocyte count, platelet count ≥ 47 G/L and age over 28 years as predictors of ST and provided a sensitivity of 77.4% and a specificity of 90.7%.

Conclusions

The generated algorithms contribute to differentiating scrub typhus from dengue fever using basic clinical and laboratory parameters, supporting clinical decision making in areas where dengue and scrub typhus are co-endemic in Vietnam.

Dengue fever is highly endemic in Vietnam, while scrub typhus is recognized as a re-emerging neglected disease. Both diseases are likely to account for more than half of the acute undifferentiated fever burden in Vietnam. However, scrub typhus is a bacterial disease requiring antimicrobial treatment, while dengue fever—of viral etiology—does not. Misdiagnosis and treatment delays cause potentially severe or fatal complications among scrub typhus patients, even though it is easily treatable. In this study, we used simple clinical and laboratory markers, which were identified upon admission of 221 PCR-confirmed scrub typhus cases and 387 NS1-positive dengue fever patients from Khanh Hoa province to identify the differences between scrub typhus and dengue. We found seven predictors that served to construct a simple clinical decision tree, holding great potential to distinguish scrub typhus from dengue using readily available clinical or laboratory findings. These predictors can strongly support medical staff in identifying scrub typhus cases from dengue, without using sophisticated diagnostic tests, and could improve the quality of diagnoses and appropriate treatment strategies at the primary health care level–especially in areas where scrub typhus and dengue fever are co-endemic in Vietnam and many parts of Asia and where diagnostic tests are not readily available.

Awareness and willingness to use HIV oral pre-exposure prophylaxis among people who inject drugs in Dar es Salaam, Tanzania: A cross-sectional survey

People who inject drugs (PWID) are at increased risk of HIV infection. Pre-exposure prophylaxis (PrEP) could help in HIV prevention among PWIDs. However, little is known about PrEP use among PWIDs in low and middle-income countries. This study reports the awareness of and willingness to use PrEP and the associated factors among PWID in Tanzania. A cross-sectional survey was conducted using respondent-driven sampling (RDS) to recruit PWIDs in Dar es Salaam, Tanzania. Data were collected using an interviewer-administered questionnaire. Chi-square statistical test was used during data analysis. The P-value of < 0.05 was used to ascertain the statistically significant relationship. IBM SPSS Statistics 25.0 was used to analyze the data. The analysis consisted of 260 PWIDs. The mean age of the respondents was 39.0 years with a standard deviation (SD) of ±7.5. Most of the respondents were male (n = 232, 89.2%) with primary education (n = 176, 67.7%). Despite the low awareness of PrEP (n = 42, 165.28%) in the study sample, the majority (n = 239, 91.9%) were willing to use PrEP. Both awareness of and willingness to use PrEP were associated with gender (p = .002 and p = < .001), awareness of HIV prevention programs(p = < .001 and p = .006), selling sex (p = .010 and p = .021), and frequency of condomless sexual intercourse (p = .029 and p = .025) respectively. In multivariable logistic regression, only gender(p = 0.046) was related to awareness of PrEP while awareness of HIV prevention programs (p = 0.009), the risk level of HIV infection(p = < .001), number of sexual partners(p = 0.046), and frequency of condomless sex(p = 0.032) were associated with willingness to use PrEP. Other factors were not statistically significant. Despite low awareness, PWIDs are highly willing to use PrEP. Future research should assess the acceptability of injectable PrEP for PWID, as their acquaintance with injection may make the formulation more practical.

Prevalence and factors associated with PTSD among female urban slum dwellers in Ibadan, Nigeria: a cross-sectional study

BACKGROUND

Little is known about the prevalence of and factors associated with PTSD among adult females in Nigeria, particularly those who live in slums. PTSD is a mental health condition that develops among some individuals who experience or witness a traumatic event. Several other factors could place individuals at heightened risk of PTSD including stress and comorbid mental disorders. Therefore, this study aimed to examine the prevalence and factors associated with PTSD among female urban slum dwellers in Ibadan, Nigeria.

METHODS

We conducted a cross sectional survey using multistage sampling of 550 women aged 18 and above from selected slums. Interviewer administered questionnaires were used to elicit information on experience of childhood trauma, recent stressors, intimate partner violence, other mental disorders, sociodemographic characteristics and PTSD. PTSD was measured using the Harvard Trauma Questionnaire (HTQ) which is based on DSM IV. A multivariable linear regression model was built to test associations between PTSD and independent variables.

RESULTS

The prevalence for PTSD was found to be 4.18% and the mean PTSD score was 5.80 ± 7.11. Sexual abuse in childhood, past year intimate partner violence and anxiety were significantly associated with higher PTSD scores. PTSD was not significantly associated with a history of recent stressors. Education, employment and marital status were not associated with PTSD however, age and wealth index showed marginal association with PTSD.

CONCLUSION

The prevalence of PTSD among women living in Ibadan slums was relatively low. Both child sexual abuse and intimate partner violence can be prevented. We also recommend longitudinal studies to better understand risk and protective factors.

Utilization of the iOS Shortcuts App to Generate a Surgical Logbook Tool: Feasibility Study

Background

Surgical audit is an essential aspect of modern reflective surgical practice and is key to improving surgical outcomes. The surgical logbook is an important method of data collection for both personal and unit audits; however, current electronic data collection tools, especially mobile apps, lack the minimum recommended data fields.

Objective

This feasibility study details the creation of a free, effective surgical logbook tool with the iOS Shortcuts app and investigates the time investment required to maintain a surgical logbook with this tool. In addition, we investigate the potential utility of the Shortcuts app in creating medical data collection tools.

Methods

Using the iOS Shortcuts app, we created a shortcut “Operation Note,” which collects surgical logbook data by using the minimum and extended audit data sets recommended by the Royal Australasian College of Surgeons. We practically assessed the feasibility of the tool, assessing the time requirement for entry, accuracy, and completeness of the entered data.

Results

The shortcut collected accurate and useful data for a surgical audit. Data entry took on average 65 seconds per case for the minimum data set, and 135 seconds per case for the extended data set, with a mean difference of 68 seconds (P<.001; 95% CI 61.6-77.7).

Conclusions

This feasibility study demonstrates the utility of the iOS Shortcuts app in the creation of a surgical logbook and the time-consuming nature of data collection for surgical audit. Our iOS Operation Note shortcut is a free, rapid, and customizable alternative to currently available logbook apps and offers surgical trainees and consultants a method for recording surgical operations, complications, and demographic data.

Towards elimination of mother-to-child transmission of HIV in Rwanda: a nested case-control study of risk factors for transmission

BACKGROUND

Mother-to-child HIV transmission (MTCT) has substantially declined since the scale-up of prevention programs around the world, including Rwanda. To achieve full elimination of MTCT, it is important to understand the risk factors associated with residual HIV transmission, defined as MTCT at the population-level that still occurs despite universal access to PMTCT.

METHODS

We performed a case control study of children born from mothers with HIV with known vital status at 18 months from birth, who were followed in three national cohorts between October and December 2013, 2014, and 2015 in Rwanda. Children with HIV were matched in a ratio of 1:2 with HIV-uninfected children and a conditional logistic regression model was used to investigate risk factors for MTCT.

RESULTS

In total, 84 children with HIV were identified and matched with 164 non-infected children. The median age of mothers from both groups was 29 years (interquartile range (IQR): 24-33). Of these mothers, 126 (51.4 %) initiated antiretroviral therapy (ART) before their pregnancy on record. In a multivariable regression analysis, initiation of ART in the third trimester (Adjusted Odds Ratio [aOR]: 9.25; 95 % Confidence Interval [95 % CI]: 2.12-40.38) and during labour or post-partum (aOR: 8.87; 95 % CI: 1.92-40.88), compared to initiation of ART before pregnancy, increased the risk of MTCT. Similarly, offspring of single mothers (aOR: 7.15; 95 % CI: 1.15-44.21), and absence of postpartum neonatal ART prophylaxis (aOR: 7.26; 95 % CI: 1.66-31.59) were factors significantly associated with MTCT.

CONCLUSIONS

Late ART initiation for PMTCT and lack of postpartum infant prophylaxis are still the most important risk factors to explain MTCT in the era of universal access. Improved early attendance at antenatal care, early ART initiation, and enhancing the continuum of care especially for single mothers is crucial for MTCT elimination in Rwanda.

Data Quality and Cost-effectiveness Analyses of Electronic and Paper-Based Interviewer-Administered Public Health Surveys: Systematic Review

Background

A population-level survey (PLS) is an essential and standard method used in public health research that supports the quantification of sociodemographic events, public health policy development, and intervention designs. Data collection mechanisms in PLS seem to be a significant determinant in avoiding mistakes. Using electronic devices such as smartphones and tablet computers improves the quality and cost-effectiveness of public health surveys. However, there is a lack of systematic evidence to show the potential impact of electronic data collection tools on data quality and cost reduction in interviewer-administered surveys compared with the standard paper-based data collection system.

Objective

This systematic review aims to evaluate the impact of the interviewer-administered electronic data collection methods on data quality and cost reduction in PLS compared with traditional methods.

Methods

We conducted a systematic search of MEDLINE, CINAHL, PsycINFO, the Web of Science, EconLit, Cochrane CENTRAL, and CDSR to identify relevant studies from 2008 to 2018. We included randomized and nonrandomized studies that examined data quality and cost reduction outcomes, as well as usability, user experience, and usage parameters. In total, 2 independent authors screened the title and abstract, and extracted data from selected papers. A third author mediated any disagreements. The review authors used EndNote for deduplication and Rayyan for screening.

Results

Our search produced 3817 papers. After deduplication, we screened 2533 papers, and 14 fulfilled the inclusion criteria. None of the studies were randomized controlled trials; most had a quasi-experimental design, for example, comparative experimental evaluation studies nested on other ongoing cross-sectional surveys. A total of 4 comparative evaluations, 2 pre-post intervention comparative evaluations, 2 retrospective comparative evaluations, and 4 one-arm noncomparative studies were included. Meta-analysis was not possible because of the heterogeneity in study designs, types, study settings, and level of outcome measurements. Individual paper synthesis showed that electronic data collection systems provided good quality data and delivered faster compared with paper-based data collection systems. Only 2 studies linked cost and data quality outcomes to describe the cost-effectiveness of electronic data collection systems. Field data collectors reported that an electronic data collection system was a feasible, acceptable, and preferable tool for their work. Onsite data error prevention, fast data submission, and easy-to-handle devices were the comparative advantages offered by electronic data collection systems. Challenges during implementation included technical difficulties, accidental data loss, device theft, security concerns, power surges, and internet connection problems.

Conclusions

Although evidence exists of the comparative advantages of electronic data collection compared with paper-based methods, the included studies were not methodologically rigorous enough to combine. More rigorous studies are needed to compare paper and electronic data collection systems in public health surveys considering data quality, work efficiency, and cost reduction.

International Registered Report Identifier (IRRID)

RR2-10.2196/10678

Outcomes of the Deployment of the Auto-Visual Acute Flaccid Paralysis Detection and Reporting (AVADAR) System for Strengthening Polio Surveillance in Africa From 2017 to 2018: Evaluation Study

Background

As we move toward a polio-free world, the challenge for the polio program is to create an unrelenting focus on smaller areas where the virus is still present, where children are being repeatedly missed, where immunity levels are low, and where surveillance is weak.

Objective

This article aimed to describe a possible solution to address weak surveillance systems and document the outcomes of the deployment of the Auto-Visual Acute Flaccid Paralysis Detection and Reporting (AVADAR) project.

Methods

This intervention was implemented in 99 targeted high-risk districts with concerns for silent polio circulation from eight countries in Africa between August 1, 2017, and July 31, 2018. A total of 6954 persons (5390 community informants and 1564 health workers) were trained and equipped with a smartphone on which the AVADAR app was configured to allow community informants to send alerts on suspected acute flaccid paralysis (AFP) and allow health worker to use electronic checklists for investigation of such alerts. The AVADAR and Open Data Kit ONA servers were at the center of the entire process. A dashboard system and coordination teams for monitoring and supervision were put in place at all levels.

Results

Overall, 96.44% (24,142/25,032) of potential AFP case alerts were investigated by surveillance personnel, yielding 1414 true AFP cases. This number (n=1414) reported through AVADAR was higher than the 238 AFP cases expected during the study period in the AVADAR districts and the 491 true AFP cases reported by the traditional surveillance system. A total of 203 out of the 1414 true AFP cases reported were from special population settings, such as refugee camps and insecure areas. There was an improvement in reporting in silent health areas in all the countries using the AVADAR system. Finally, there were 23,473 reports for other diseases, such as measles, diarrhea, and cerebrospinal meningitis, using the AVADAR platform.

Conclusions

This article demonstrates the added value of AVADAR to rapidly improve surveillance sensitivity. AVADAR is capable of supporting countries to improve surveillance sensitivity within a short interval before and beyond polio-free certification.

Electronic data capture for large scale typhoid surveillance, household contact tracing, and health utilisation survey: Strategic Typhoid Alliance across Africa and Asia

Electronic data capture systems (EDCs) have the potential to achieve efficiency and quality in collection of multisite data. We quantify the volume, time, accuracy and costs of an EDC using large-scale census data from the STRATAA consortium, a comprehensive programme assessing population dynamics and epidemiology of typhoid fever in Malawi, Nepal and Bangladesh to inform vaccine and public health interventions. A census form was developed through a structured iterative process and implemented using Open Data Kit Collect running on Android-based tablets. Data were uploaded to Open Data Kit Aggregate, then auto-synced to MySQL-defined database nightly. Data were backed-up daily from three sites centrally, and auto-reported weekly. Pre-census materials' costs were estimated. Demographics of 308,348 individuals from 80,851 households were recorded within an average of 14.7 weeks range (13-16) using 65 fieldworkers. Overall, 21.7 errors (95% confidence interval: 21.4, 22.0) per 10,000 data points were found: 13.0 (95% confidence interval: 12.6, 13.5) and 24.5 (95% confidence interval: 24.1, 24.9) errors on numeric and text fields respectively. These values meet standard quality threshold of 50 errors per 10,000 data points. The EDC's total variable cost was estimated at US$13,791.82 per site. In conclusion, the EDC is robust, allowing for timely and high-volume accurate data collection, and could be adopted in similar epidemiological settings.

The role of the Stop Transmission of Polio (STOP) program in developing countries: the experience of Kenya

Background

In 1988, the 41^st World Health Assembly (WHA) marked the launch of the Global Polio Eradication Initiative (GPEI) for the eradication of polio. A key component of the GPEI has been the development and deployment of a skilled workforce to implement eradication activities. In 1989, the Stop Transmission of Polio (STOP) was initiated to address skilled human resource gaps and strengthen poliovirus surveillance. This paper describes the role of the STOP 52 team in technical capacity building and health system strengthening in the implementation of polio eradication strategies in Kenya following the outbreak of Circulating Vaccine-derived Poliovirus type 2 (cVDPV2).

Methods

Overview of the STOP program, deployment, and the modality of support are described. Descriptive analysis was conducted using data collected by the STOP 52 team during integrated supportive supervisory visits conducted from July 2018 to September 2019. Analyses were carried out using Epi-Info statistical software (Version 7.0) and maps were developed using Quantum Geographic Information System (Q-GIS) (version 3.12.0).

Results

The STOP 52 team supportively supervised 870 health facilities on Expanded Program on Immunization (EPI), and Acute Flaccid Paralysis (AFP) and other Vaccine-Preventable Diseases (VPDs) surveillance in 16 (34.1%) of the 47 counties during the study period. AFP surveillance was conducted in all health facilities supervised leading to the detection and investigation of 11 unreported AFP cases. The STOP 52 team, as part of the outbreak response, provided technical support to five successive rounds of polio Supplementary Immunization Activities (SIAs) conducted during the study period. Moreover, in addressing programmatic data needs, the STOP 52 Data Manager played a valuable role in enhancing the quality and use of data for evidence-based planning and decision-making. The STOP 52 team contributed to the development of operational plans, guidelines and training manuals, and participated in the delivery of various Training of Trainers (TOT) and On-the-Job Training (OJT) on EPI, AFP and other VPDs surveillance including data management.

Conclusion

The STOP 52 team has contributed to polio eradication efforts in Kenya by enhancing AFP and other VPDs surveillance, supporting polio SIAs, strengthening EPI, use of quality EPI, AFP and other VPDs data, and capacity building of Frontline Health Workers (FLWs). The use of Open Data Kit (ODK) technology during supportive supervision, and AFP and other VPDs surveillance was found to be advantageous. A national STOP program should be modeled to produce a homegrown workforce to ensure the availability of more sustainable technical support for polio eradication efforts in Kenya and possibly other polio-affected countries.

Electronic data capture for large scale typhoid surveillance, household contact tracing, and health utilisation survey: Strategic Typhoid Alliance across Africa and Asia

Electronic data capture systems (EDCs) have the potential to achieve efficiency and quality in collection of multisite data. We quantify the volume, time, accuracy and costs of an EDC using large-scale census data from the STRATAA consortium, a comprehensive programme assessing population dynamics and epidemiology of typhoid fever in Malawi, Nepal and Bangladesh to inform vaccine and public health interventions. A census form was developed through a structured iterative process and implemented using Open Data Kit Collect running on Android-based tablets. Data were uploaded to Open Data Kit Aggregate, then auto-synced to MySQL-defined database nightly. Data were backed-up daily from three sites centrally, and auto-reported weekly. Pre-census materials’ costs were estimated. Demographics of 308,348 individuals from 80,851 households were recorded within an average of 14.7 weeks range (13-16) using 65 fieldworkers. Overall, 21.7 errors (95% confidence interval: 21.4, 22.0) per 10,000 data points were found: 13.0 (95% confidence interval: 12.6, 13.5) and 24.5 (95% confidence interval: 24.1, 24.9) errors on numeric and text fields respectively. These values meet standard quality threshold of 50 errors per 10,000 data points. The EDC’s total variable cost was estimated at US$13,791.82 per site. In conclusion, the EDC is robust, allowing for timely and high-volume accurate data collection, and could be adopted in similar epidemiological settings.