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Many countries do not have enough medical equipment and infrastructure to tackle this challenge. Due to the lack of a\u00a0central administration to\u00a0guide the countries to take the necessary precautions, they do not proactively identify the cases in advance. This has caused Covid-19 cases to be on the increase, with\u00a0the number of cases\u00a0increasing at a geometric progression. Rapid testing, RT-PCR testing, and a CT-Scan\/X-Ray of the chest are the primary procedures in identifying the\u00a0covid-19 disease. Proper immunization is delivered on a priority basis based on the instances discovered in order to preserve human lives. In this research\u00a0paper, we suggest a technique for identifying covid-19 positive cases and determine the most affected locations of covid-19 cases for vaccine distribution in order to limit the disease's impact. To handle the aforementioned issues, we propose a cloud based image analysis approach\u00a0for using a\u00a0COVID-19 vaccination distribution (CIA-CVD) model. The model uses a\u00a0deep learning, machine learning, digital image processing and cloud solution to deal with the\u00a0increasing cases of COVID-19 and its priority wise distribution of the vaccination.<\/jats:p><jats:p><jats:bold>Graphical Abstract<\/jats:bold><\/jats:p>","DOI":"10.1186\/s13677-023-00539-y","type":"journal-article","created":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T03:01:47Z","timestamp":1700708507000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["CIA-CVD: cloud based image analysis for COVID-19 vaccination distribution"],"prefix":"10.1186","volume":"12","author":[{"given":"Vivek Kumar","family":"Prasad","sequence":"first","affiliation":[]},{"given":"Debabrata","family":"Dansana","sequence":"additional","affiliation":[]},{"given":"S Gopal Krishna","family":"Patro","sequence":"additional","affiliation":[]},{"given":"Ayodeji Olalekan","family":"Salau","sequence":"additional","affiliation":[]},{"given":"Divyang","family":"Yadav","sequence":"additional","affiliation":[]},{"given":"Madhuri","family":"Bhavsar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,23]]},"reference":[{"key":"539_CR1","doi-asserted-by":"crossref","unstructured":"Song Y, Zheng S, Li L, Zhang X, Zhang X, Huang Z, Chen J, Zhao H, Jie Y, Wang R, Chong Y (2020) Deep learning enables accurate diagnosis of novel coronavirus (COVID-19) with CT images. medRxiv","DOI":"10.1109\/TCBB.2021.3065361"},{"key":"539_CR2","first-page":"200905","volume":"19","author":"L Li","year":"2020","unstructured":"Li L, Qin L, Xu Z, Yin Y, Wang X, Kong B, Bai J, Lu Y, Fang Z, Song Q, Cao K (2020) Artificial intelligence distinguishes COVID-19 from community acquired pneumonia on chest CT. 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