Child development study: Evaluation of effectiveness of low cost, high frequency and high-quality data to identify the main constraints and drivers of childhood and adolescence development in Malawi

Phuka, John

Child development study: Evaluation of effectiveness of low cost, high frequency and high-quality data to identify the main constraints and drivers of childhood and adolescence development in Malawi

Date

2021-01-13

Authors

Phuka, John

Publisher

Kamuzu University of Health Sciences

Abstract

Background This a cohort study with multiple end point to evaluation impact of digital technologies of determinants of child growth and development. Problem: In developing countries like Malawi, children are trapped in a cycle that, from the getgo, offers them very limited opportunities to escape poverty and under-development. Malawian children will grow up in an environment without basic nutrients to properly develop and might potentially die from diseases that could have been otherwise prevented at low cost. This cycle can only be broken if the right interventions for each child reach them at the right time. Given hard resource constraints, this requires evaluating trade-offs based on what are the most cost-effective interventions to address each of the issues hindering child development in each setting. However due poor data collection in poor countries, programs targeted at children and adolescents often have to be scaled up or down in the absence of rigorous evidence about their impacts. Lately poor modelling data from reliable data has made it difficult to reliably model pattern of Malawian epidemics. High frequency social-behavioural data will enable Malawi make more accurate estimations and models based of unbiased data independently determined by digital sensors. Aim and Objectives Our study aims to assess impact of high frequent data collection using wearable digital technologies. Specifically our objective is to evaluate impact of real-time program evaluation through multiple; to assess effectiveness of high frequency data on children’s non-invasive biomarkers (from heart rate and variability to brain waves) and symptoms; and to determine social interaction between parents and children and other social contacts (including caregiver-child interactions); and impact of health promotion For example, we can analyse how handwashing habits can reduce the spread of infections like COVID-19. Further the study will evaluate the impacts of these messages on the behaviours and symptoms tracked by phone surveys, with the ability to understand trends and calibrate interventions in real-time. Methods The study is longitudinal prospective cohort with nested intervention study on health promotion. Data collection includes socioeconomic and behavioural data with end point non-invasive biomarkers. In combination with rapid experimentation, these data allows policies to be evaluated in real time. With the help of machine learning algorithms, the data also feeds early warning systems to empower community health workers to detect problems at an early stage – especially when it comes to epidemics like COVID-19 – and to implement immediate and preventive measures to address them. Last, combining experimentation with predictions allows for program personalization, such that each child and adolescent can benefit from the interventions most likely to benefit them. Expected Findings Like during the extensive pilot phase over the course of 2019, we have shown that this approach is able to collect high-frequency, high-quality and inexpensive data by adapting wearable sensors and phone surveys to the local setting specificities. Early results are encouraging, but further investigation to document how real-time program evaluation and personalization can be scaled up with the help of the right technologies and under the appropriate legal and ethical framework. The social-behavioural data based on contact sensors will likely model pattern of care for child stimulation as well as pattern of likely spread of diseases like diarrhoea, upper respiratory tract infection (like COVID 19 and common viral colds). This study will be especially important and beneficial under the current epidemic shock of COVID-19. Health promotion intervention through sending mobile nudges (reminders and encouragement messages) through SMS will allow us determine factors associated with behaviour output and help resolve compliance challenges to adherence to preventive behaviours to infections (lately we see decline in COVID-19 prevention measure irrespective awareness campaigns) Dissemination of Findings The findings will be disseminated through peer research conferences, publication in peer reviewed journals and COMREC. The data will be made public after peer reviewed journal are published for possible re-analysis and teaching.