Browsing by Author "Phuka, John"

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    Assessing breastfeeding and complimentary feeding practices during COVID-19.
    (Kamuzu University of Health Sciences, 21-08-11) Phuka, John
    Study type: Mixed methods cross-sectional study Problem: The corona virus disease (COVID-19) has had severe consequences on the social aspects of human interaction. Particularly, measures aimed at deterring the spread of disease such as social distancing and wearing of masks have likely hindered infant and young child feeding and care practices including breast feeding, child and mother interaction as well as family or community participatory support. Breast feeding is essential for children’s optimal physical and cognitive growth, especially in settings highly burdened with malnutrition. Monitoring of breastfeeding and complementary feeding practices during the pandemic is critical to ensure that women can continue to breastfeed their children safely and mitigate the risks of malnutrition. However, care practices of infants and children in the context of pandemic have not been well studied. Therefore, this study aims to pilot our modified questionnaire on breastfeeding knowledge and practices as well as obtain essential data on infant and young child feeding practices Methodology: The study will recruit 415 participants from Nkhata Bay and Lilongwe. Enumeration areas will be randomly selected from each district, thereafter households with children aged 0-24 months will be identified through community leaders and health surveillance officers. Data will be collected from mothers or care givers of children through a structured questionnaire and focus group discussions. Expected results and dissemination: Study outcomes may inform national nutrition programming, the global maternal nutrition reports and other key advocacy reports on exclusive breast feeding and complementary feeding practices during the pandemic. The findings of this research will be presented to United National Children’s Emergency Fund (UNICEF), DNHA, Ministry of Health and relevant stakeholders. A completed final report of the study will be submitted to UNICEF, DNHA, COMREC and MoH.
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    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
    (Kamuzu University of Health Sciences, 2022-07-26) Phuka, John
    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.
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    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
    (Kamuzu University of Health Sciences, 2021-01-13) Phuka, John
    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.