Impact of cross border reverse migration in Delhi–UP region of India during COVID-19 lockdown
The declaration of a nationwide lockdown in India led to millions of migrant workers, particularly from Uttar Pradesh (UP) and Bihar, returning to their home states without proper transportation and social distancing from cities such as Delhi, Mumbai, and Hyderabad. This unforeseen migration and soc...
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| Format: | Article |
| Language: | English |
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De Gruyter
2023-07-01
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| Series: | Computational and Mathematical Biophysics |
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| Online Access: | https://doi.org/10.1515/cmb-2022-0151 |
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| author | Dwivedi Shubhangi Perumal Saravana Keerthana Kumar Sumit Bhattacharyya Samit Kumari Nitu |
| author_facet | Dwivedi Shubhangi Perumal Saravana Keerthana Kumar Sumit Bhattacharyya Samit Kumari Nitu |
| author_sort | Dwivedi Shubhangi |
| collection | DOAJ |
| description | The declaration of a nationwide lockdown in India led to millions of migrant workers, particularly from Uttar Pradesh (UP) and Bihar, returning to their home states without proper transportation and social distancing from cities such as Delhi, Mumbai, and Hyderabad. This unforeseen migration and social mixing accelerated the transmission of diseases across the country. To analyze the impact of reverse migration on disease progression, we have developed a disease transmission model for the neighboring Indian states of Delhi and UP. The model’s essential mathematical properties, including positivity, boundedness, equilibrium points (EPs), and their linear stability, as well as computation of the basic reproduction number (R0)\left({R}_{0}), are studied. The mathematical analysis reveals that the model with active reverse migration cannot reach a disease-free equilibrium, indicating that the failure of restrictive mobility intervention caused by reverse migration kept the disease propagation alive. Further, PRCC analysis highlights the need for effective home isolation, better disease detection techniques, and medical interventions to curb the spread. The study estimates a significantly shorter doubling time for exponential growth of the disease in both regions. In addition, the occurrence of synchronous patterns between epidemic trajectories of the Delhi and UP regions accentuates the severe implications of migrant plight on UP’s already fragile rural health infrastructure. By using COVID-19 incidence data, we quantify key epidemiological parameters, and our scenario analyses demonstrate how different lockdown plans might have impacted disease prevalence. Based on our observations, the transmission rate has the most significant impact on COVID-19 cases. This case study exemplifies the importance of carefully considering these issues before implementing lockdowns and social isolation throughout the country to combat future outbreaks. |
| first_indexed | 2024-03-12T22:07:30Z |
| format | Article |
| id | doaj.art-d91bb38ae59644db82ca6c576980a7bd |
| institution | Directory Open Access Journal |
| issn | 2544-7297 |
| language | English |
| last_indexed | 2024-03-12T22:07:30Z |
| publishDate | 2023-07-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Computational and Mathematical Biophysics |
| spelling | doaj.art-d91bb38ae59644db82ca6c576980a7bd2023-07-24T11:18:28ZengDe GruyterComputational and Mathematical Biophysics2544-72972023-07-0111176077610.1515/cmb-2022-0151Impact of cross border reverse migration in Delhi–UP region of India during COVID-19 lockdownDwivedi Shubhangi0Perumal Saravana Keerthana1Kumar Sumit2Bhattacharyya Samit3Kumari Nitu4School of Mathematical and Statistical Sciences, Indian Institute of Technology Mandi, Himachal Pradesh, 175005, IndiaDepartment of Physics, School of Natural Sciences, Shiv Nadar Institution of Eminence, Uttar Pradesh, IndiaSchool of Mathematical and Statistical Sciences, Indian Institute of Technology Mandi, Himachal Pradesh, 175005, IndiaDepartment of Mathematics, Disease Modelling Lab, School of Natural Sciences, Shiv Nadar Institution of Eminence, Uttar Pradesh, IndiaSchool of Mathematical and Statistical Sciences, Indian Institute of Technology Mandi, Himachal Pradesh, 175005, IndiaThe declaration of a nationwide lockdown in India led to millions of migrant workers, particularly from Uttar Pradesh (UP) and Bihar, returning to their home states without proper transportation and social distancing from cities such as Delhi, Mumbai, and Hyderabad. This unforeseen migration and social mixing accelerated the transmission of diseases across the country. To analyze the impact of reverse migration on disease progression, we have developed a disease transmission model for the neighboring Indian states of Delhi and UP. The model’s essential mathematical properties, including positivity, boundedness, equilibrium points (EPs), and their linear stability, as well as computation of the basic reproduction number (R0)\left({R}_{0}), are studied. The mathematical analysis reveals that the model with active reverse migration cannot reach a disease-free equilibrium, indicating that the failure of restrictive mobility intervention caused by reverse migration kept the disease propagation alive. Further, PRCC analysis highlights the need for effective home isolation, better disease detection techniques, and medical interventions to curb the spread. The study estimates a significantly shorter doubling time for exponential growth of the disease in both regions. In addition, the occurrence of synchronous patterns between epidemic trajectories of the Delhi and UP regions accentuates the severe implications of migrant plight on UP’s already fragile rural health infrastructure. By using COVID-19 incidence data, we quantify key epidemiological parameters, and our scenario analyses demonstrate how different lockdown plans might have impacted disease prevalence. Based on our observations, the transmission rate has the most significant impact on COVID-19 cases. This case study exemplifies the importance of carefully considering these issues before implementing lockdowns and social isolation throughout the country to combat future outbreaks.https://doi.org/10.1515/cmb-2022-0151sars-cov-2npis failuremigrated laboursdoubling timephase synchronizationparameter estimationscenario analysisprcc analysis34d0634d2037m05 |
| spellingShingle | Dwivedi Shubhangi Perumal Saravana Keerthana Kumar Sumit Bhattacharyya Samit Kumari Nitu Impact of cross border reverse migration in Delhi–UP region of India during COVID-19 lockdown Computational and Mathematical Biophysics sars-cov-2 npis failure migrated labours doubling time phase synchronization parameter estimation scenario analysis prcc analysis 34d06 34d20 37m05 |
| title | Impact of cross border reverse migration in Delhi–UP region of India during COVID-19 lockdown |
| title_full | Impact of cross border reverse migration in Delhi–UP region of India during COVID-19 lockdown |
| title_fullStr | Impact of cross border reverse migration in Delhi–UP region of India during COVID-19 lockdown |
| title_full_unstemmed | Impact of cross border reverse migration in Delhi–UP region of India during COVID-19 lockdown |
| title_short | Impact of cross border reverse migration in Delhi–UP region of India during COVID-19 lockdown |
| title_sort | impact of cross border reverse migration in delhi up region of india during covid 19 lockdown |
| topic | sars-cov-2 npis failure migrated labours doubling time phase synchronization parameter estimation scenario analysis prcc analysis 34d06 34d20 37m05 |
| url | https://doi.org/10.1515/cmb-2022-0151 |
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