IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 565 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 AN ANALYTICAL HIERARCHY PROCESS APPROACH FOR A COVID-19 RISK ASSESSMENT STUDY AMID THE LATEST RE-OPEN AND UNLOCK PHASE IN INDIA Arpan Garg Research scholar; Dept. of Mathematics & Scientific Computing National Institute of Technology Hamirpur, India arpan1996garg@gmail.com Talari Ganesh Assistant Professor; Dept. of Mathematics & Scientific Computing National Institute of Technology Hamirpur, India ganimsc2007@gmail.com ABSTRACT The long duration of the COVID-19 pandemic has now compelled people to come out of their cells and begin engaging in various activities using different modes and in different places, which involves a high risk of being infected by COVID-19. This work aims to analyze the degree of the risk involved in such activities with the implementation of the latest re-open and unlock phase in India, the second most COVID-19 affected country. Seven important activities and the mode and place of conducting these activities are considered as the main criteria and sub-criteria of this study. The responses are formed with a pairwise comparison matrix, and an Analytical Hierarchy Process (AHP) approach is used to calculate the criteria/sub-criteria weights. An integrated AHP analysis output representation consisting of the degree of risk, grades, ranking, and major reasons of risk for each criterion and sub-criteria of this work is presented. This risk assessment study may help identify risky activities so that people can choose other available alternatives. Keywords: COVID-19; AHP; risk assessment; MCDM; Decision-making 1. Introduction The novel corona virus (COVID-19), or Syndrome Corona Virus-2 (SARS-CoV-2), originated in Wuhan City of Hubei province in China and has become a worldwide pandemic (Wang et al., 2020). The common symptoms of COVID-19 include dry cough, fever, malaise, and headache (Wang et al., 2020) which are normal symptoms of sickness as the seasons change which makes it tedious to verify unless a check-up for COVID-19 is done. The WHO has found that an infected person can transmit the virus to others who are within 6 feet. However, recent studies have found that possible virus transmission can occur over a distance of 2 meters (Setti et al., 2020). As of 10:10 GMT, October 10, 2020, Worldometer (2020) had reported over 37,155,642 confirmed cases including 1,073,338 deaths worldwide. According to the registered data, the United States of America, Brazil and India are most COVID-19 affected nations. To prevent a possibly mailto:arpan1996garg@gmail.com mailto:ganimsc2007@gmail.com IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 566 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 more critical situation, the government of India ordered a nationwide lockdown (2020) on March 24, 2020 which initially came into force for 21 days starting on March 25, 2020 (Lockdown implementation order, 2020). Due to the lockdown implementation, all important but non-essential activities such as traveling, gathering, use of delivery services, entertainment activities, and many other important activities from a financial point of view were stopped. In order to maintain social distancing, a series of unlock phases was soon started due to the financial and management requirements. Phase 4 re-open and unlock was announced through the Ministry of Home Affairs website on August 29, 2020, which allows various activities to take place with some restrictions. The exponential increase in the number of cases and casualties has become a major concern for all the health bodies including the WHO and the Indian Council for Medical Research (ICMR) because for the last few days, India has continuously recorded more than 75,000 cases per day (Worldometer, 2020). The easing of restrictions for conducting various essential activities that was issued in the latest phase of unlock guidelines are applicable to more than 1.38 billion citizens of India (Population of India, 2020) which potentially increases the COVID-19 risk. This situation has motivated the authors to conduct a risk assessment study for many important daily life activities. This study aims to calculate the risk involved in many activities that are likely to take place in this phase of unlock. In this work, the authors tried to list various activities, and the mode and place of conducting these activities with their relative risk of COVID-19 infection. The authors have applied the Analytical Hierarchy Process (AHP) with the row geometric mean method (Crawford and Williams, 1985) to calculate relative risk weights of the main criteria and sub-criteria. The activities and mode or place of conducting an activity are considered as criteria and sub-criteria, respectively in this study. The risk weight of the criteria/sub-criteria helps identify extremely risky activities. 2. Focus of the work SARS-CoV-2 has become one of the worst healthcare emergencies that does not yet have a promising treatment or vaccination available, which makes a relative risk assessment of various activities and the places of conducting these activities very important to minimize the fatal growth rate of infections. This work highlights seven main activities that are necessary for normal living and likely to take place in response to the latest re-open and unlock phase. The seven activities include job, shopping, gathering, entertainment, traveling, residency, and utilizing delivery services and have been listed as our main criteria. The various modes and places of conducting these activities based on their expected strength and possibility of contact with different people are considered as the sub-criteria of this study. The main criteria and sub-criteria with their notations are listed in Table 1. In this work, the standard layer hierarchy and the proper hierarchical structure representing all of the main criteria and sub-criteria of this study are respectively shown in Figures1 and 2. The analyzed risk of conducting the main activities are listed in Table 2 and the cumulative risk weight, ranking, and description as well as the major factors and reasons are discussed in Table 3. This work helps people understand the risk involved in the mode of conducting an activity at some particular place so that available IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 567 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 alternatives can be considered or the activity can be avoided. It is important to remain safe and clear during this pandemic period. Table 1 Main criteria and their sub-criteria Criteria Sub-criteria Job 1 A Hospital 11 A , Government office 12 A , Private office 13 A Shop 2A Grocery store 21A , Vendor 22A , Shopping mall 23A Gathering 3 A Marriage ceremony 31 A , Cremation ceremony 32 A , Conference and seminar 33 A , Worship place 34 A Entertainment 4A Stadium 41A , Movie hall 42A , Zoo and water park 43A Traveling 5 A Personal vehicle 51 A , Bus, Train and Taxi 52 A , Airline and ship 53 A Residency 6 A Joint family 61 A , Nuclear family 62 A , Hosteller 63 A Utilizing delivery Services 7 A Food delivery 71 A , E-commerce 72 A 3. AHP solution The Analytical Hierarchy Process (AHP), developed by Saaty (1977), is a highly practical procedure that helps solve complex multicriteria decision making (MCDM) problems. The AHP hierarchy structure is a three layer structure (Chaiyaphan and Ransikarbum, 2020) as shown in Figure 1, where the top, middle and final layer of the hierarchy structure are i) Goal or Target ii) Criteria, Sub-criteria (if any), and iii) Possible choice or solution to the problem, respectively. Figure 1 Hierarchy structure of AHP IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 568 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 The AHP has widely been used in healthcare, risk assessment, construction, supply chain, automotive, and many other fields by researchers and statisticians. Simon et al. (2019) applied the AHP model for priority analysis of various strategies for malaria control. Improta et al. (2019) applied the AHP for health technology assessment (HTA) of optoelectronic biosensors for oncology. Rajak and Shaw (2019) performed an AHP analysis for evaluation and selection on mobile health (mHealth) applications. Also, the AHP has been an impressive support system for researchers in risk assessment studies. Lyu et al. (2020) used Fuzzy AHP in the risk assessment of mega city infrastructure, and Rivera et al. (2020) applied the AHP to study the risk factors for the spread of COVID-19 in Peru. The application of the AHP requires the sequential fulfillment of several major steps (Rosenbloom, 1997) listed below: 1. Break down the problem into a hierarchy of a finite number of decision elements. 2. Compute the pairwise comparison values for all possible pairs of criteria at every level of the hierarchy structure and construct a pairwise comparison matrix with tolerable inconsistency. According to Saaty (1977), the degree of inconsistency can be measured using the expressions given below: 1 max    n CI n RI CI CR  where, CI is the consistency index; max  is the largest Eigen value; n is the number of criteria; CR is the consistency ratio, and a RI value 0.58, 0.9 and 1.32 for 4,3n and 7 respectively, is the suggested random index value (Saaty, 1987). It is suggested that the CR value must be less than 0.1. 3. Compute the preference weight using the suitable AHP analysis. For a pairwise comparison matrix   ij aA  , th i row geometric mean (Crawford and Williams, 1985) value is: nn j iji aw 1 1            4. Rank the decision criteria after aggregating the relative weights. IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 569 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 Table 2 Pairwise comparison of main criteria, normalized weight and grade Criteria 1A 2A 3A 4A 5A 6A 7A Criteria weights Grades Consistency check Job 1 A 1 3 1 2 2 6 5 0.2677 A Shopping 2 A 0.33 1 0.5 1 0.33 3 3 0.1043 D Gathering 3 A 1 2 1 4 2 5 4 0.2632 B 0.0327CI Entertainment 4 A 0.5 1 0.25 1 0.5 2 2 0.0947 E 0.0242 =CR Travelling 5 A 0.5 3 0.5 2 1 4 3 0.1745 C 1.32 =RI Residency 6 A 0.1667 0.33 0.2 0.5 0.25 1 0.5 0.0408 G Utilizing delivery services 7 A 0.2 0.33 0.25 0.5 0.33 2 1 0.0548 F IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 570 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 Figure 2 Hierarchy of activities and their respective places 4. Results and discussion The authors have identified seven important activities as the main criteria of this risk assessment study. These activities were specifically chosen by considering the latest gathering restrictions in the Phase 4 re-open and unlock (2020) guidelines issued by the Ministry of Home Affairs. Also, the mode and place of conducting these selected activities have been identified as their sub-criteria and are shown in Table 1. Since the AHP is able to provide very reliable output for complex multicriteria decision making (MCDM) problems with little mathematical computation, the authors were able to perform all of the analysis manually using the row geometric mean method with precision (Crawford and Williams, 1985). IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 571 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 The authors observed that the opinions of different health experts regarding how safe/unsafe a location is are subject to the presence or absence of some pre-determined factors. Generally, medical experts/doctors would be the most likely people to provide responses for a healthcare study such as this; however, since they are required to perform their duties to every possible extent during this pandemic the authors have identified some major factors that are favorable to COVID-19 virus transmission as follows: i) A high population density or a large number of people present/involved in an activity, ii) Maintaining less than 6 feet of social-distancing, and iii) Physically close and frequent contact among people. Next, the pairwise comparison matrix was shaped by an expert data analyst and statistician based on their experience and understanding of the correlation of identified factors with the criteria and sub-criteria of this study. A consistency analysis was used to ensure that the PCM was tolerably inconsistent. The degree of risk involved in a criterion was calculated as criteria weight by applying the row geometric mean method. All of the criteria were assigned a grade from A to G based on their high to low degree of risk; this is shown in Table 2. Moreover, the pairwise comparison matrices, consistency-checks, and relative weights for all of the sub-criteria within the same level of the hierarchy are shown in Table 4. This AHP analysis for a COVID-19 risk assessment presents an integrated outcome representation in Table 3. This representation includes all criteria and sub-criteria with their degree of COVID-19 risk in the form of criteria and sub-criteria weight, the cumulative sub-criteria weight derived by multiplication of local sub-criteria weight with their respective main criteria weight which leads to form a global sub-criteria weight and ranking. The authors have also expressed various expected reasons of risk involvement in this representation. Table 3 Integrated outcome representation with expected major reasons of risk S.NO Criteria /Sub-criteria Criteria weight Sub- criteria weight Cumulative normalized Sub- criteria weight Grade and ranking Expected major reasons of risk 1 A Job 0.267682 A Frequent contact with external objects makes it the most serious activity of the study 11 A Hospital 0.745006 0.199425 1 Being in direct contact with virus infected patients, health care workers like doctors, nurses and others are at extreme risk of COVID-19 12 A Government office 0.098552 0.026380 14 Need for continuous operational state for proper implementation of guidelines 13 A Private office 0.156441 0.041876 9 The limited space available and lack of sanitization facilities in many private offices 2 A Shopping 0.104275 D The basic requirement of goods and other materials has resulted in shopping as a main criterion 21 A Grocery store 0.196246 0.020463 17 The reach to a limited number of customers from a specific territory makes shopping at grocery stores less risky than shopping at vendors or the mall 22 A Vendors 0.49223 0.051327 7 Covering a very large area of the city increases the risk of being in contact with the virus 23 A Shopping mall 0.311522 0.032484 11 Finite, but sufficiently large customer capacity 3 A Gathering 0.263216 B A gathering is the second most risky activity because meeting with a large group of people IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 572 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 proportionally increases the probability of COVID- 19 infection 31 A Marriage ceremony 0.222189 0.058483 4 Permission for 50 people gathering at a marriage ceremony 32 A Cremation ceremony 0.119379 0.031422 12 Permission for at most 20 people gathering at a cremation ceremony 33 A Conference and seminar 0.200771 0.052846 6 Large participation in a conference and seminar 34 A Worship place 0.457659 0.120463 2 High visiting frequency and the non registering nature of a worship place 4 A Entertainment 0.094716 E Need for a healthy mood and good physical health are very essential at this time which demands that entertainment be one of the main criterion of this study 41 A Stadium 0.196976 0.018656 18 The risk of coming in contact with sports equipment that may carry the virus, yet stadiums have sufficient space for maintaining distance from others 42 A Movie hall 0.311239 0.029479 13 The density of the audience in a movie hall is very high and increases the risk 43 A Zoo and water park 0.491783 0.046580 8 Possible infection through animals and contaminated water 5 A Travelling 0.174485 C A list of requirements demands that one travel by various modes of transportation, which makes it an essential criterion of this study 51 A Personal vehicle 0.122542 0.021381 16 Traveling by personal vehicle eliminates many possibilities of infection, yet their maintenance requires visits to many public places 52 A Bus, Train and Taxi 0.319130 0.0556835 5 Use of the same seats by many people and high capacity of commuters, categorizes use of a bus, train, and taxi as extremely risky 53 A Airline and ship 0.558326 0.097419 3 Overseas origin of passengers from various countries and a very large capacity of these modes of transportations are the main reasons for the extreme risk. 6 A Residency 0.040795 G The residency area of an individual with a number of people is a major concern of this study; however, the AHP analysis finds that it has optimal risk involvement 61 A Joint family 0.537895 0.021943 15 A large number of family members makes it slightly risky 62 A Nuclear family 0.297788 0.012148 20 Small number of family members is the main reason for a nuclear family to have the second to last position in most risky sub-criteria 63 A Hosteller 0.164315 0.006703 21 Being a hosteller is the last ranked sub-criteria with the minimum risk involved 7 A Utilizing delivery services 0.054828 F Utilization of various resources without going out is the main reason for inclusion of various delivery and online purchase facilities under the category of ‘Utilizing delivery services’ in this study 71 A Food delivery 0.666666 0.036552 10 Involvement of many hands from cooking to delivery 72 A E-commerce 0.333334 0.018276 19 Careful and standard measures, but the product visits many stations IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 573 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 Table 4 Pair wise comparison of sub-criteria with consistency check and weight Criteria Sub- criteria Sub- criteria weight Consistency check 1 A 11 A 12 A 13 A 11 A 1 6 6 0.745006 0.0268=CI 12 A 0.1667 1 0.5 0.098552 0.046=CR 13 A 0.1667 2 1 0.156441 2 A 21 A 22 A 23 A 21 A 1 0.5 0.5 0.196246 0.0269=CI 22 A 2 1 2 0.492230 0.0464=CR 23 A 2 0.5 1 0.311522 3 A 31 A 32 A 33 A 34 A 31 A 1 2 1 0.5 0.222189 32 A 0.5 1 0.5 0.33 0.119379 0.0136 =CI 33 A 1 2 1 0.33 0.200771 0.0151=CR 34 A 2 3 3 1 0.457659 4 A 41 A 42 A 43 A 41 A 1 0.5 0.5 0.196976 0.0268=CI 42 A 2 1 0.5 0.311239 0.0462 =CR 43 A 2 2 1 0.491783 5 A 51 A 52 A 53 A 51 A 1 0.33 0.25 0.122542 0.0077=CI 52 A 3 1 0.5 0.319130 0.0133=CR 53 A 4 2 1 0.558326 6 A 61 A 62 A 63 A 61 A 1 2 3 0.537895 0.0027CI 62 A 0.5 1 2 0.297788 0.0047CR 63 A 0.33 0.5 1 0.164315 7 A 71 A 72 A 71 A 1 2 0.666666 0CI 72 A 0.5 1 0.333334 IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 574 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 5. Conclusions COVID-19 is spreading exponentially and for a developing country like India with a population of 1.38 billion (Population of India, 2020) it has become an extremely tedious health care management problem. The government of India has promptly responded to the pandemic and imposed a nationwide lockdown (2020). Many restrictions have been eased in a sequence of re-open and unlock phases. In the latest Phase 4 re-open and unlock (2020) guidelines, the authors have observed that large gatherings, interstate transportation, utilization of various delivery services and many other activities are no longer under strict control which might be responsible for a sudden increase in COVID- 19 cases. To analyze the degree of COVID-19 risk involved in many important activities through different modes and at different places, the authors conducted a COVID-19 risk assessment using a very popular MCDM technique, the Analytic Hierarchy Process (AHP). A simple and structured application of the AHP has derived very significant outcomes. The risk assessment reflects that doing a job has the highest risk of COVID-19 infection among all seven listed activities because it requires frequent contact with external objects that may carry COVID-19. Moreover, gathering is an occasional event, but has the potential possibility of COVID-19 transmission to a large number of people coming from different places which makes it the second most risky activity of the study, followed by traveling, shopping, entertainment, utilizing delivery services and residency. The authors found that cumulative sub-criteria weights and global sub-criteria ranking were very helpful in identifying the most risky places to conduct the corresponding activity. Based on the rankings, the hospital is the most risky work station and healthcare workers such as doctors, nurses and other medical staff are at extreme risk of COVID-19 infection because they are in direct contact with COVID-19 patients. The absence of proper identification and record placement policies and the frequency of visiting are the expected reasons for a place of worship to be the second most risky sub-criteria of this study. All of the other sub-criteria and their global rankings and major reasons for risk are explained in Table 3. The authors also conclude that being a hosteller and living in a nuclear family are two of the least risky sub-criteria when compared to others. In this COVID-19 risk assessment, the authors tried to express the real time suitability of the AHP approach. The authors suggest that many other healthcare management problems can be analyzed with a large number of different activities in future. This study can potentially help select a suitable alternative activity or mode and place of conducting an activity to avoid various risk factors involved with the parent activity. IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 575 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 REFERENCES Badillo- Rivera, E., Fow-Esteves, A., Alata-Lopez, F., Viru-Vasquez, P., &Acuña, M. (2020). Environmental and social analysis as risk factors for the spread of the novel coronavirus (SARS-CoV-2) using remote sensing, GIS and analytical hierarchy process (AHP): Case of Peru. medRxiv, preprint. Doi: https://doi.org/10.1101/2020.05.31.20118653 Chaiyaphan, C., &Ransikarbum, K. (2020). Criteria analysis of food safety using the Analytic Hierarchy Process (AHP)- a case study of Thailand’s fresh markets. E3S Web of Conferences, 141, 02001. Doi: https://doi.org/10.1051/e3sconf/202014102001 Crawford, G., & Williams, C. (1985). A note on the analysis of subjective judgment matrices. Journal of Mathematical Psychology, 29(4), 387-405. Doi: https://doi.org/10.1016/0022-2496(85)90002-1 Lockdown implementationorder (2020). Available :https://www.mha.gov.in/sites/default/files/PR_NationalLockdown_26032020_0.pdf Improta, G., Perrone, A., Russo, M. A., & Triassi, M. (2019).Health technology assessment (HTA) of optoelectronic biosensors for oncology by analytic hierarchy process (AHP) and Likert scale. BMC Medical Research Methodology, 19(1), 140. Doi: https://doi.org/10.1186/s12874-019-0775-z Lyu, H. M., Shen, S. L., Zhou, A., & Yang, J. (2020). Risk assessment of mega-city infrastructures related to land subsidence using improved trapezoidal FAHP. Science of The Total Environment, 717, 135310. Doi: https://doi.org/10.1016/j.scitotenv.2019.135310 Phase 4 re-open and unlock (2020).Availablehttps://www.mha.gov.in/sites/default/files/MHAOrder_Unlock4_290820 20.pdf Population of India (2020).Available: https://www.worldometers.info/worldpopulation/india-population/. Rajak, M., & Shaw, K. (2019).Evaluation and selection of mobile health (mHealth) applications using AHP and fuzzy TOPSIS. Technology in Society, 59, 101186. Doi: https://doi.org/10.1016/j.techsoc.2019.101186 Rosenbloom, E. S. (1997). A probabilistic interpretation of the final rankings in AHP. European Journal of Operational Research, 96(2), 371-378. Doi: https://doi.org/10.1016/s0377-2217(96)00049-5 Saaty, R. W. (1987). The analytic hierarchy process—what it is and how it is used. Mathematical Modelling, 9(3-5), 161-176. Doi: https://doi.org/10.1016/0270- 0255(87)90473-8 https://www.mha.gov.in/sites/default/files/PR_NationalLockdown_26032020_0.pdf https://www.mha.gov.in/sites/default/files/MHAOrder_Unlock4_29082020.pdf https://www.mha.gov.in/sites/default/files/MHAOrder_Unlock4_29082020.pdf https://www.worldometers.info/worldpopulation/india-population/ IJAHP Article: Garg, Ganesh/An Analytical Hierarchy Process approach for a COVID-19 risk assessment study amid the latest re-open and unlock phase in India International Journal of the Analytic Hierarchy Process 576 Vol. 12 Issue 3 2020 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v12i3.814 Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234-281. Doi: https://doi.org/10.1016/0022- 2496(77)90033-5 Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European Journal of Operational Research, 48(1), 9-26. Doi: https://doi.org/10.1016/0377- 2217(90)90057-i Setti, L., Passarini, F., De Gennaro, G., Barbieri, P., Perrone, M. G., Borelli, M., ...&Miani, A. (2020). Airborne transmission route of COVID-19: why 2 meters/6 feet of inter-personal distance could not be enough. International Journal of Environmental Research and Public Health.17(8): 2932. Doi: 10.3390/ijerph17082932 Simon, J., Adamu, A., Abdulkadir, A., & Henry, A. S. (2019). Analytical Hierarchy Process (AHP) model for prioritizing alternative strategies for malaria control. Asian Journal of Probability and Statistics, 1-8. Doi: https://doi.org/10.9734/ajpas/2019/v5i130124 Wang, C., Horby, P. W., Hayden, F. G., &Gao, G. F. (2020). A novel coronavirus outbreak of global health concern. The Lancet, 395(10223), 470-473. Doi: https://doi.org/10.1016/s0140-6736(20)30185-9 Worldometers.COVID-19 Coronavirus pandemic. Available: https://www.worldometers.info/coronavirus/country./India/. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215485/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215485/ https://dx.doi.org/10.3390%2Fijerph17082932 https://www.worldometers.info/coronavirus/country./India/