Impact of COVID-19 vaccinations in India: a state-wise analysis
Abstract Background Ever since the emergence of COVID-19 and its consequent spread across continents, engulfing both advanced and developing nations, COVID-19 vaccine was considered to be the main weapon to curb the spread of the virus. The COVID-19 vaccination program in India started after the fir...
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BMC
2025-01-01
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| Online Access: | https://doi.org/10.1186/s12889-025-21401-7 |
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| author | Abhigayan Adhikary Manoranjan Pal Raju Maiti |
| author_facet | Abhigayan Adhikary Manoranjan Pal Raju Maiti |
| author_sort | Abhigayan Adhikary |
| collection | DOAJ |
| description | Abstract Background Ever since the emergence of COVID-19 and its consequent spread across continents, engulfing both advanced and developing nations, COVID-19 vaccine was considered to be the main weapon to curb the spread of the virus. The COVID-19 vaccination program in India started after the first wave of infections (March – December 2020) had almost subsided. Objective In this work, the objective is to perform a state-wise analysis to assess the impact of vaccination in slowing down the spread of infections during the second COVID-19 wave (February – October 2021) in India. The prediction accuracy of the proposed model with the optimal lag length (in days) after including the impact of vaccination is evaluated and compared with a model without it. A total of 21 states are chosen for the analysis encompassing 97% of the Indian population. Methods We use the generalized Gompertz curve to study the COVID-19 outbreak. The generalized Gompertz model is then further modified to study the impact of vaccination to slow down the spread of COVID-19. The modified model considers the cumulative proportion of individuals having the first COVID-19 vaccine shot in each state as the explanatory variable. Results By incorporating the impact of vaccination in the Generalized Gompertz Curves, it is seen that the visible impact of the first dose of the vaccination is observed after a lag of 20 days with 16 out of the 21 states showing the impact of vaccines in curbing the spread of COVID-19. However, in states like Telangana, West Bengal, Tamil Nadu, Rajasthan, and Kerala, we do not conclusively observe the impact of vaccination during the study period. Conclusions Using only COVID-19 infection cases and the vaccination data in the proposed model, we conclude that overall, the vaccination program effectively curbed the spread of COVID-19 in India. |
| format | Article |
| id | doaj-art-4bea9ba786984359949bf4ec682a0f4c |
| institution | Kabale University |
| issn | 1471-2458 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| spelling | doaj-art-4bea9ba786984359949bf4ec682a0f4c2025-01-26T12:55:43ZengBMCBMC Public Health1471-24582025-01-0125111010.1186/s12889-025-21401-7Impact of COVID-19 vaccinations in India: a state-wise analysisAbhigayan Adhikary0Manoranjan Pal1Raju Maiti2Economic Research Unit, Indian Statistical InstituteEconomic Research Unit, Indian Statistical InstituteEconomic Research Unit, Indian Statistical InstituteAbstract Background Ever since the emergence of COVID-19 and its consequent spread across continents, engulfing both advanced and developing nations, COVID-19 vaccine was considered to be the main weapon to curb the spread of the virus. The COVID-19 vaccination program in India started after the first wave of infections (March – December 2020) had almost subsided. Objective In this work, the objective is to perform a state-wise analysis to assess the impact of vaccination in slowing down the spread of infections during the second COVID-19 wave (February – October 2021) in India. The prediction accuracy of the proposed model with the optimal lag length (in days) after including the impact of vaccination is evaluated and compared with a model without it. A total of 21 states are chosen for the analysis encompassing 97% of the Indian population. Methods We use the generalized Gompertz curve to study the COVID-19 outbreak. The generalized Gompertz model is then further modified to study the impact of vaccination to slow down the spread of COVID-19. The modified model considers the cumulative proportion of individuals having the first COVID-19 vaccine shot in each state as the explanatory variable. Results By incorporating the impact of vaccination in the Generalized Gompertz Curves, it is seen that the visible impact of the first dose of the vaccination is observed after a lag of 20 days with 16 out of the 21 states showing the impact of vaccines in curbing the spread of COVID-19. However, in states like Telangana, West Bengal, Tamil Nadu, Rajasthan, and Kerala, we do not conclusively observe the impact of vaccination during the study period. Conclusions Using only COVID-19 infection cases and the vaccination data in the proposed model, we conclude that overall, the vaccination program effectively curbed the spread of COVID-19 in India.https://doi.org/10.1186/s12889-025-21401-7COVID-19Disease modellingGeneralized Gompertz CurvesForecastingTime SeriesVaccinations |
| spellingShingle | Abhigayan Adhikary Manoranjan Pal Raju Maiti Impact of COVID-19 vaccinations in India: a state-wise analysis BMC Public Health COVID-19 Disease modelling Generalized Gompertz Curves Forecasting Time Series Vaccinations |
| title | Impact of COVID-19 vaccinations in India: a state-wise analysis |
| title_full | Impact of COVID-19 vaccinations in India: a state-wise analysis |
| title_fullStr | Impact of COVID-19 vaccinations in India: a state-wise analysis |
| title_full_unstemmed | Impact of COVID-19 vaccinations in India: a state-wise analysis |
| title_short | Impact of COVID-19 vaccinations in India: a state-wise analysis |
| title_sort | impact of covid 19 vaccinations in india a state wise analysis |
| topic | COVID-19 Disease modelling Generalized Gompertz Curves Forecasting Time Series Vaccinations |
| url | https://doi.org/10.1186/s12889-025-21401-7 |
| work_keys_str_mv | AT abhigayanadhikary impactofcovid19vaccinationsinindiaastatewiseanalysis AT manoranjanpal impactofcovid19vaccinationsinindiaastatewiseanalysis AT rajumaiti impactofcovid19vaccinationsinindiaastatewiseanalysis |