Model Description:
The Bayesian network models the level of Severely Malnourished Children. This model considers the type of delivery, the care/attention provided to the child and the mother, and what form of nourishment is provided, and considering all this tries to analyze the number of Severely Malnourished Children.
The malnourishment data is reported based on children that are registered in Anganawadis.
Nodes/Attributes
The above model is based on the following nodes. The color scheme used represents the type of node/attribute. (Purple – Independent node; Orange – Dependent node; Red – Target node)
| Node/Attribute | Description | Data Source |
| No. of new-born children_1353 | Total number of children born recently | KAG 2020-21 |
| Total Anganawadi Centres_1512 | Number of Anganwadi Centers | KAG 2020-21 |
| No. of Anganawadi Workers_1523 | Number of Anganwadi Workers | KAG 2020-21 |
| No. of Anganawadi Helpers_1524 | Number of Anganwadi Helpers | KAG 2020-21 |
| No. of Beneficiaries availed Janani Suraksha Yojana (JSY)_1338 | No. of pregnant women availing the scheme | KAG 2020-21 |
| No. of institutional deliveries_1350 | No. of pregnant women delivering in a hospital | KAG 2020-21 |
| No. of deliveries at home_1351 | No. of pregnant women delivering at home | KAG 2020-21 |
| Total No. of Children in Anganwadi_1525 | No. of children enrolled in Anganwadi s | KAG 2020-21 |
| Total number of new-born children breastfed within one hour_1356 | Total number of new-born children breastfed within one hour | KAG 2020-21 |
| Total number of live babies weighed at birth_1357 | Total number of live babies weighed at birth | KAG 2020-21 |
| Number of breastfeeding children receiving adequate diet_1365 | Number of breastfeeding children who received adequate diet for nutrition | KAG 2020-21 |
| Low birth weight babies reported (less than 2500g)_1358 | New born babies with weight less than 2500 gm | KAG 2020-21 |
| Severely Malnourished_1528 (Target Variable) | Number of babies who are severely malnourished | KAG 2020-21 |
Intervention Modeling
It sets the network variables to specific levels, to track the changes in the target variable in the network. For instance: If we fix the value of the variable ‘Number of Beneficiaries availed Janani Suraksha Yojana_1338’ to ‘high’, then we would study the impact of this intervention on the target variable i.e., “Severely Malnourished_1528″ of the network across varieties of Taluks in Karnataka.
| Intervention Code | Intervening Node | Description | Ease of Intervention [1-most difficult, 5-easy] | Total Models Impacted | Models Impacted | Domains Impacted | Data Stories impacted upon intervention |
| I1 | Number of Beneficiaries availed Janani Suraksha Yojana _1338 | Increasing the number of beneficiaries that avail the JSY scheme in order to assess the nutritional health of a newborn child. Beneficiaries can be increased by spending more resources on deploying more ASHA workers and spreading awareness amongst the general public. | 3 | 4 | 1. Maternal Deaths 2. Child Malnutrition 3. Child Stunting 4. Child Wasting | Health | |
| I2 | Total Anganawadi Centres_1512 | Increasing the number of Anganawadi centers with the aim of registering more newborn children and their mothers under the Anganawadi system and seeing what impact it has on the nutritional health of the child. | 4 | 2 | 1. Child Stunting 2. Child Wasting | Health | |
| I3 | No. of Anganawadi Workers_1523 | Increasing the number of Anganawadi Workers with the aim of providing better care to more newborn children and their mothers that have registered in an Anganawadi and seeing how much of a positive impact it has on the nutritional health of the child. | 4 | 2 | 1. Child Stunting 2. Child Wasting | Health | 1. Children – Anaemia, Stunting, Under-weight & Wasting |
| I4 | Total Anthyodaya Ration Card Holders_32 | By increasing the ratio of the number of Anthyodaya ration card holders to People BPL we can determine whether the benefits provided by the Anthyodaya scheme are actually beneficial in improving children’s nutritional health. Can also be used to adjust the benefits provided by the scheme so that nutritional needs are better met. | 3 | 2 | 1. Child Stunting 2. Child Wasting | Health | 1. Children – Anaemia, Stunting, Under-weight & Wasting |
| I5 | No. of institutional deliveries_1350 | By promoting institutional deliveries through schemes and ads not limited to but including JSY we can aim at educating women on child nourishment and the care to be taken to ensure nourishment through counseling by doctors and professionals at the hospitals. | 4 | 4 | 1. Maternal Deaths 2. Child Malnutrition 3. Child Stunting 4. Child Wasting | Health |
DISCLAIMER: AI predictive models are meant to support and augment expert decision-making, and not a replacement for the same. It is important for AI model predictions to be vetted by domain experts before committing to action