Dataset Information

Spatiotemporal Analysis for COVID-19 Delta Variant Using GIS-Based Air Parameter and Spatial Modeling.

ABSTRACT: The coronavirus disease of 2019 (COVID-19) pandemic is currently a global challenge, with 210 countries, including Indonesia, seeking to minimize its spread. Therefore, this study aims to determine the spatiotemporal spread pattern of this virus in Surabaya using various data on confirmed cases from 28 April to 26 October 2021. It also aims to determine the relationship between pollutant parameters, such as carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3), as well as the government's high social restrictions policy in Java-Bali. Several methods, such as the weighted mean center, directional distribution, Getis-Ord Gi*, Moran's I, and geographically weighted regression, were used to identify the spatial spread pattern of the virus. The weighted mean center indicated that the epicenter location of the outbreak moved randomly. The directional distribution demonstrated a decrease of 21 km2 at the end of the study phase, which proved that its spread has significantly reduced in Surabaya. Meanwhile, the Getis-Ord Gi* results demonstrated that the eastern and southern parts of the study region were highly infected. Moran's I demonstrate that COVID-19 cases clustered during the spike. The geographically weighted regression model indicated a number of influence zones in the northeast, northwest, and a few in the southwest parts at the peak of R2 0.55. The relationship between COVID-19 cases and air pollution parameters proved that people living at the outbreak's center have low pollution levels due to lockdown. Furthermore, the lockdown policy reduced CO, NO2, SO2, and O3. In addition, increase in air pollutants; namely, NO2, CO, SO2 and O3, was recorded after 7 weeks of lockdown implementation (started from 18 August).

SUBMITTER: Cahyadi MN

PROVIDER: S-EPMC8835317 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Spatiotemporal Analysis for COVID-19 Delta Variant Using GIS-Based Air Parameter and Spatial Modeling.

Cahyadi Mokhamad Nur MN Handayani Hepi Hapsari HH Warmadewanthi Idaa I Rokhmana Catur Aries CA Sulistiawan Soni Sunarso SS Waloedjo Christrijogo Sumartono CS Raharjo Agus Budi AB Endroyono Atok Mohamad M Navisa Shilvy Choiriyatun SC Wulansari Mega M Jin Shuanggen S

International journal of environmental research and public health 20220130 3

The coronavirus disease of 2019 (COVID-19) pandemic is currently a global challenge, with 210 countries, including Indonesia, seeking to minimize its spread. Therefore, this study aims to determine the spatiotemporal spread pattern of this virus in Surabaya using various data on confirmed cases from 28 April to 26 October 2021. It also aims to determine the relationship between pollutant parameters, such as carbon monoxide (CO), nitrogen dioxide (NO<sub>2</sub>), sulfur dioxide (SO<sub>2</sub>), ...[more]

PMID: 35162634

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Project description:Originating from Wuhan, China, COVID-19 is spreading rapidly throughout the world. The transmission rate is reported to be high for this novel strain of coronavirus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as compared to its predecessors. Major strategies in terms of clinical trials of medicines and vaccines, social distancing, use of personal protective equipment (PPE), and so on are being implemented in order to control the spread. The current study concentrates on lockdown and social distancing policy followed by the Indian Government and evaluates its effectiveness using Bayesian probability model (BPM). The change point analysis (CPA) done through the above approach suggests that the states which implemented the lockdown before the exponential rise of cases are able to control the spread of the disease in a much better and efficient way. The analysis has been done for states of Maharashtra, Gujarat, Madhya Pradesh, Rajasthan, Tamil Nadu, West Bengal, Uttar Pradesh, and Delhi as union territory. The highest value of Δ (delta) is reported for Gujarat and Madhya Pradesh with a value of 9.6 weeks, while the lowest value is 4.7, evidently for Maharashtra which is the worst affected. All of the states indicate a significant correlation (p < 0.05, tstat > tcritical) for Δ, i.e., the difference in the time period of CPA and lockdown with cases per population (CPP) and cases per unit area (CPUA), while weak correlation (p < 0.1 and tstat < tcritical) is exhibited by delta and cases per unit population density (CPD). For both CPP and CPUA, tstat > tcritical indicating a significant correlation, while Pearson's correlation indicates the direction to be negative. Further analysis in terms of identification of high-risk areas has been studied from the Voronoi approach of GIS based on the inputs from BPM. All the states follow the above pattern of high population, high case scenario, and the boundaries of risk zones can be identified by Thiessen polygon (TP) constructed therein. The findings of the study help draw strategic and policy-driven response for India, toward tackling COVID-19 pandemic.

Project description:BackgroundThe B.1.617.2 (delta) variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (Covid-19), has contributed to a surge in cases in India and has now been detected across the globe, including a notable increase in cases in the United Kingdom. The effectiveness of the BNT162b2 and ChAdOx1 nCoV-19 vaccines against this variant has been unclear.MethodsWe used a test-negative case-control design to estimate the effectiveness of vaccination against symptomatic disease caused by the delta variant or the predominant strain (B.1.1.7, or alpha variant) over the period that the delta variant began circulating. Variants were identified with the use of sequencing and on the basis of the spike (S) gene status. Data on all symptomatic sequenced cases of Covid-19 in England were used to estimate the proportion of cases with either variant according to the patients' vaccination status.ResultsEffectiveness after one dose of vaccine (BNT162b2 or ChAdOx1 nCoV-19) was notably lower among persons with the delta variant (30.7%; 95% confidence interval [CI], 25.2 to 35.7) than among those with the alpha variant (48.7%; 95% CI, 45.5 to 51.7); the results were similar for both vaccines. With the BNT162b2 vaccine, the effectiveness of two doses was 93.7% (95% CI, 91.6 to 95.3) among persons with the alpha variant and 88.0% (95% CI, 85.3 to 90.1) among those with the delta variant. With the ChAdOx1 nCoV-19 vaccine, the effectiveness of two doses was 74.5% (95% CI, 68.4 to 79.4) among persons with the alpha variant and 67.0% (95% CI, 61.3 to 71.8) among those with the delta variant.ConclusionsOnly modest differences in vaccine effectiveness were noted with the delta variant as compared with the alpha variant after the receipt of two vaccine doses. Absolute differences in vaccine effectiveness were more marked after the receipt of the first dose. This finding would support efforts to maximize vaccine uptake with two doses among vulnerable populations. (Funded by Public Health England.).

Project description:BackgroundWith the emergence of the delta variant, the United States experienced a rapid increase in Covid-19 cases in 2021. We estimated the risk of breakthrough infection and death by month of vaccination as a proxy for waning immunity during a period of delta variant predominance.MethodsCovid-19 case and death data from 15 U.S. jurisdictions during January 3 to September 4, 2021 were used to estimate weekly hazard rates among fully vaccinated persons, stratified by age group and vaccine product. Case and death rates during August 1 to September 4, 2021 were presented across four cohorts defined by month of vaccination. Poisson models were used to estimate adjusted rate ratios comparing the earlier cohorts to July rates.ResultsDuring August 1 to September 4, 2021, case rates per 100,000 person-weeks among all vaccine recipients for the January to February, March to April, May to June, and July cohorts were 168.8 (95% confidence interval [CI], 167.5 to 170.1), 123.5 (95% CI, 122.8 to 124.1), 83.6 (95% CI, 82.9 to 84.3), and 63.1 (95% CI, 61.6 to 64.6), respectively. Similar trends were observed by age group for BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) vaccine recipients. Rates for the Ad26.COV2.S (Janssen-Johnson & Johnson) vaccine were higher; however, trends were inconsistent. BNT162b2 vaccine recipients 65 years of age or older had higher death rates among those vaccinated earlier in the year. Protection against death was sustained for the mRNA-1273 vaccine recipients. Across age groups and vaccine types, people who were vaccinated 6 months ago or longer (January-February) were 3.44 (3.36 to 3.53) times more likely to be infected and 1.70 (1.29 to 2.23) times more likely to die from COVID-19 than people vaccinated recently in July 2021.ConclusionsOur study suggests that protection from SARS-CoV-2 infection among all ages or death among older adults waned with increasing time since vaccination during a period of delta predominance. These results add to the evidence base that supports U.S. booster recommendations, especially for older adults vaccinated with BNT162b2 and recipients of the Ad26.COV2.S vaccine. (Funded by the Centers for Disease Control and Prevention.).

Dataset Information

Spatiotemporal Analysis for COVID-19 Delta Variant Using GIS-Based Air Parameter and Spatial Modeling.

Publications

Spatiotemporal Analysis for COVID-19 Delta Variant Using GIS-Based Air Parameter and Spatial Modeling.

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