During the COVID-19 pandemic, allocation plan of ventilators is reinforced for fulfilling its critical needs to the hospitals. The death rate caused by COVID-19 could have been diminished globally if the proposed medical logistics network is possible to be timely deployed between suppliers and demand regions. Owing to operate and organize medical logistics network and to minimize the total delivery time (TDT), we have formulated a mathematical model based on mixed-integer non-linear programming (MINLP). The application of the proposed model is considered employing the real-life pandemic data, which is alarmed to the severely affected regions in India. The results denote that the anticipated model of medical logistics network efficiently performs in a pandemic demand scenario. The responsiveness of the developed model is also examined under three demand scenarios based on Covid-19 pandemic wave-1, wave-2, and wave-3. Lastly, the sensitivity analyses are done to examining the impact of the critical parameters of the model, and findings are discussed.

During the pandemic, the indigenous distribution plan of ventilators has been heightened to fulfil urgent hospital requirements. In this study, we have proposed a Global Ventilator Supply Chain Distribution Network (GVSCDN). The deployment of such a model can reduce deaths caused by ventilator scarcity during a deadly pandemic, as observed globally during COVID-19. To demonstrate and deploy GVSCDN, we formulated a Mixed-Integer Non-Linear Programming model to minimize the Total Delivery Time of ventilator distribution using multimodal transportation. Additionally, the developed model has been solved using the Chemical Reaction Optimization (CRO) algorithm. The applications of the proposed mathematical model have been investigated using real-life COVID-19 data related to all states and union territories of India. The results indicate that the proposed design of GVSCDN effectively works in a pandemic under multiple problem instances. Also, examine the responsiveness of the proposed model under randomly generated instances. Finally, the sensitivity analyses have been accomplished by investigating the impact of the model’s essential parameters, such as loading time, unloading time, and speed of the vehicles.

People in rural areas suffer due to lack of proper health care specifically during the emergency condition. Ontime delivery of emergency lifesaving medicine at the remote area is a one of the major concerns and one of the major reasons for this cause is the negligence and lack of proper transportation and road infrastructure. In this paper we have proposed a mixed integer non-linear programming (MINLP) model that is based on drone delivery for end-to-end local supply chain distribution network to ensure the fastest possible delivery of lifesaving medicine at the remote area. Moreover, we have used the Dijkstra algorithm to find the shortest path to deliver the lifesaving medicine at the patient home location using drone. The objective of this paper is to design an end-to-end local supply chain network to minimize the total delivery lead time of the lifesaving medicines under emergencies conditions. Also, the proposed MINLP model help to select the optimal healthcare facility location to minimize the total delivery lead time.

In India, the operation of public health system is hampered by quality and accessibility of the available data collected at various sites across the country. Effective implementation of health programs like National Health Mission (NHM) is a big challenge for the Indian government as well as public health professionals because it’s very difficult to monitor each and every activity at ground level due to lack of skilled human resource. There are various health programs on Disease Surveillance, Family Planning, Reproductive and Child Health, Vector Borne Diseases, Iodine Deficiency Disorder, Leprosy, Blindness, HIV/AIDS and Tuberculosis under NHM governed by separate divisions in the Union Health Ministry, India. Data is published separately by these divisions and made available to officials for the response, action, planning and policy making. In this paper, we introduce a technology-driven model of strengthening public health activities through the Internet of Things (IoT) in India by providing data on public health activities at one place. This would help to monitor the activities at different levels of the healthcare system and respond in a timely manner. Implementation of IoT through installation of sensors across Primary and Community Health Centers (PHCs and CHCs), District and Specialized Hospitals and Government Medical Colleges to maintain the routine data collected on the health activities under different national programs. This would consequently transmit the data to the centralized server of Central Ministry of Health & Family Welfare, India where data would be processed and provide information so that the trends of diseases across the country could be understood in a timely, effective and clear manner. This would help the ministry officials and public health professionals to prioritize the situation and take necessary steps. The proposed technology framework is a large chain of smart equipments where the entered data can be stored and processed. The devices then transmit the data for analysis to the main server of the Central Health Ministry to provide alerts on the trends of diseases in a timely manner. After the observation of disease trends,the necessary steps of mitigation and prevention across the nation could be taken. This would also facilitate to inform the people during a natural disaster. IoT would help to identify few hidden factors that would be a responsible for effective implementation or hinder the program process. Considering the present situation in India, the IoT based Smart disease surveillance system (SDSS) would be a considerable intervention in the field of Public Health. In the current situation, data is reported on weekly interval and the national health officials dependent on the local health units for the reports. This type of smart device system would change the scenario of data reporting and decrease the burden of the district and the state health officials by registering with the Central Health Ministry server for the IoT based smart device and timely update their records and reduce the under-reporting of cases.