Child development study (CDS: 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
Loading...
Date
2022-07-26
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Kamuzu University of Health Sciences
Abstract
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 tradeoffs
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 earlywarning 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.
Description
Type of study: This a cohort study with multiple end point to evaluation impact of digital technologies of determinants
of child growth and development.