Evidence map›Paper›PMID 36945723›Full record

ArticleGroundwater for sustainable development2023

Insight into vaccination and meteorological factors on daily COVID-19 cases and mortality in Bangladesh.

Mohammad Nayeem Hasan, Md Aminul Islam, Sarawut Sangkham, Adhena Ayaliew Werkneh, Foysal Hossen, Md Atiqul Haque, Mohammad Morshad Alam, Md Arifur Rahman, Sanjoy Kumar Mukharjee, Tahmid Anam Chowdhury and 5 more

Abstract read
In one paragraph

Article in Groundwater for sustainable development, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Effects of fine particulate matter (PMCase studies in chemical and environmental engineering · 2023
    Article
  9. Article
  10. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Mohammad Nayeem HasanDepartment of Statistics, Shahjalal University of Science & Technology, Sylhet, Bangladesh.
Md Aminul IslamCOVID-19 Diagnostic Lab,Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
Sarawut SangkhamDepartment of Environmental Health, School of Public Health, University of Phayao, Muang District, 56000, Phayao, Thailand.
Adhena Ayaliew WerknehDepartment of Environmental Health, School of Public Health, College of Health Sciences, Mekelle University, P. O. Box 1871, Mekelle, Ethiopia.
Foysal HossenCOVID-19 Diagnostic Lab,Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
Md Atiqul HaqueKey Lab of Animal Epidemiology and Zoonoses of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, China.
Mohammad Morshad AlamHealth, Nutrition and Population Global Practice, The World Bank, Dhaka, 1207, Bangladesh.
Md Arifur RahmanCOVID-19 Diagnostic Lab,Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
Sanjoy Kumar MukharjeeCOVID-19 Diagnostic Lab,Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
Tahmid Anam ChowdhuryDepartment of Geography and Environment, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh.
Juan Eduardo Sosa-HernándezTecnologico de Monterrey, School of Engineering and Sciences, Monterrey, 64849, Mexico.
Md JakariyaDepartment of Environmental Science and Management, North South University, Bashundhara, Dhaka, 1229, Bangladesh.
Firoz AhmedCOVID-19 Diagnostic Lab,Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
Prosun BhattacharyaCOVID-19 Research @KTH, Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, Teknikringen 10B, SE-100 44, Stockholm, Sweden.
Samuel Asumadu SarkodieNord University Business School (HHN), Post Box 1490, 8049, Bodø, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing COVID-19 contagious disease caused by SARS-CoV-2 has disrupted global public health, businesses, and economies due to widespread infection, with 676.41 million confirmed cases and 6.77 million deaths in 231 countries as of February 07, 2023. To control the rapid spread of SARS-CoV-2, it is crucial to determine the potential determinants such as meteorological factors and their roles. This study examines how COVID-19 cases and deaths changed over time while assessing meteorological characteristics that could impact these disparities from the onset of the pandemic. We used data spanning two years across all eight administrative divisions, this is the first of its kind--showing a connection between meteorological conditions, vaccination, and COVID-19 incidences in Bangladesh. We further employed several techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Auto-Regressive Integrated Moving Average with explanatory variables (ARIMAX), and Automatic forecasting time-series model (Prophet). We further analyzed the effects of COVID-19 vaccination on daily cases and deaths. Data on COVID-19 cases collected include eight administrative divisions of Bangladesh spanning March 8, 2020, to January 31, 2023, from available online servers. The meteorological data include rainfall (mm), relative humidity (%), average temperature (°C), surface pressure (kPa), dew point (°C), and maximum wind speed (m/s). The observed wind speed and surface pressure show a significant negative impact on COVID-19 cases (-0.89, 95% confidence interval (CI): 1.62 to -0.21) and (-1.31, 95%CI: 2.32 to -0.29), respectively. Similarly, the observed wind speed and surface pressure show a significant negative impact on COVID-19 deaths (-0.87, 95% CI: 1.54 to -0.21) and (-3.11, 95%CI: 4.44 to -1.25), respectively. The impact of meteorological factors is almost similar when vaccination information is included in the model. However, the impact of vaccination in both cases and deaths model is significantly negative (for cases: 1.19, 95%CI: 2.35 to -0.38 and for deaths: 1.55, 95%CI: 2.88 to -0.43). Accordingly, vaccination effectively reduces the number of new COVID-19 cases and fatalities in Bangladesh. Thus, these results could assist future researchers and policymakers in the assessment of pandemics, by making thorough efforts that account for COVID-19 vaccinations and meteorological conditions.

Indexed as

BangladeshCOVID-19Mathematical modelsMeteorological factorsSARS-CoV-2Temperature and rainfallVaccination

Identifiers

PMID36945723
PMCPMC9977696

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.