Modeling a COVID-19 Vaccination Campaign in the State of Madhya Pradesh, India.

COVID-19 vaccination campaigns have been launched across the globe to mitigate the impact of the COVID-19 disease. However, COVID-19 vaccination campaigns (Vaccination campaigns are the complete process of COVID-19 vaccination campaigns beyond just administrating vaccines.) are a complex multi-stakeholder process, and therefore, it is important to understand the key components and drivers of vaccination campaigns to help devise strategies to increase vaccination coverage for existing and future vaccination efforts. A system dynamics modeling approach was used to trace the vaccination campaign for the Indian state of Madhya Pradesh. The results identified the key stakeholders of the vaccination campaign and their inter-linkages, and the diverse perspectives of stakeholders of vaccination campaigns in Madhya Pradesh were collated in a structured format. Further, system dynamics models were developed to capture all aspects of the vaccination campaign in Madhya Pradesh, including the challenges and innovations. The outcomes of the study can assist academicians, practitioners, and policymakers develop vaccination programs at sub-national, national, and global levels. They will guide decision-makers to take preemptive measures to mitigate possible risks and challenges and provide improved services as part of vaccination campaigns. Supplementary Information: The online version contains supplementary material available at 10.1007/s40171-022-00326-9.

Strengthening the immunization supply chain: A time-to-supply based approach to cold chain network optimization & extension in Madhya Pradesh.

Expansion of immunization coverage is dependent in part on delivering potent vaccines in an equitable and timely manner to immunization outreach session sites from Cold Chain Points (CCPs). When duration of travel between the last CCP and the session site (Time-to-Supply) is too long, three consequences may arise: decreased potency due to exposure to heat and freezing, beneficiary dropouts due to delayed session starts, and, increased operational costs for the Health Facility (HF) conducting the outreach sessions. Guided by the Government of India's recommendation on cold chain point expansion to ensure that all session sites are within a maximum of 60 min from the last CCP, CHAI and the State Routine Immunization Cell in the state of Madhya Pradesh collaborated to pilot a novel approach to cold chain network optimization and expansion in eight districts of Madhya Pradesh. Opportunities for realignment of remote sub-health centers (SHCs) and corresponding session sites to alternative existing CCPs or to HFs which could be converted to new CCPs were identified, and proposed using a greedy adding algorithm-based optimization which relied on health facility level geo-location data. Health facility geo-coordinates were collected through tele-calling and site visits, and a Microsoft Excel based optimization tool was developed. This exercise led to an estimated reduction in the number of remote SHCs falling beyond the permissible travel time from CCPs by 56.89 percent (132 remote sites), from 232 to 100. The 132 resolved sites include 73 sites realigned to existing CCPs, and 59 sites to be attached to 22 newly proposed CCPs. Both the network optimization approach and the institutional capacity built during this project will continue to be useful to India's immunization program. The approach is replicable and may be leveraged by developing countries facing similar challenges due to geographical, institutional, and financial constraints.