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      Impact of Extreme Hot Climate on COVID‐19 Outbreak in India

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          Abstract

          Coronavirus Disease 2019 (COVID‐19) pandemic poses extreme threat to public health and economy, particularly to the nations with higher population density. The disease first reported in Wuhan, China; later, it spreads elsewhere, and currently, India emerged as COVID‐19 hotspot. In India, we selected 20 densely populated cities having infection counts higher than 500 (by 15 May) as COVID‐19 epicenters. Daily COVID‐19 count has strong covariability with local temperature, which accounts approximately 65–85% of the explained variance; i.e., its spread depends strongly on local temperature rise prior to community transmission phase. The COVID‐19 cases are clustered at temperature and humidity ranging within 27–32°C and 25–45%, respectively. We introduce a combined temperature and humidity profile, which favors rapid COVID‐19 growth at the initial phase. The results are highly significant for predicting future COVID‐19 outbreaks and modeling cities based on environmental conditions. On the other hand, CO 2 emission is alarmingly high in South Asia (India) and entails high risk of climate change and extreme hot summer. Zoonotic viruses are sensitive to warming induced climate change; COVID‐19 epicenters are collocated on CO 2 emission hotspots. The COVID‐19 count distribution peaks at 31.0°C, which is 1.0°C higher than current (2020) and historical (1961–1990) mean, value. Approximately, 72% of the COVID‐19 cases are clustered at severe to record‐breaking hot extremes of historical temperature distribution spectrum. Therefore, extreme climate change has important role in the spread of COVID‐19 pandemic. Hence, a strenuous mitigation measure to abate greenhouse gas (GHG) emission is essential to avoid such pandemics in future.

          Key Points

          • The survival and growth of SARS‐CoV‐2 in the environment have tighter association with ambient temperature and relative humidity

          • Approximately 72% of the COVID‐19 cases in India are clustered in severe record‐breaking hot extreme of historical temperature distribution spectrum

          • Extreme climate change has an important role in the spread of COVID‐19 pandemic in India

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Chaolin Huang, Yeming Wang, Xingwang Li … (2020)
          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Clinical Characteristics of Coronavirus Disease 2019 in China

            Wei-jie Guan, Zheng-yi Ni, Yu Hu … (2020)
            Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)
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              A Novel Coronavirus from Patients with Pneumonia in China, 2019

              Na Zhu, Dingyu Zhang, Wenling Wang … (2020)
              Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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                Author and article information

                Contributors
                Debashis Nath:
                ORCID: https://orcid.org/0000-0001-9299-2729
                nathd@mail.sysu.edu.cn , debashis.narl@gmail.com
                Journal
                Journal ID (nlm-ta): Geohealth
                Journal ID (iso-abbrev): Geohealth
                Journal ID (doi): 10.1002/(ISSN)2471-1403
                Journal ID (publisher-id): GH2
                Title: GeoHealth
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Electronic): 2471-1403
                Publication date Collection: December 2020
                Publication date (Electronic): 01 December 2020
                Volume: 4
                Issue: 12 ( doiID: 10.1002/gh2.v4.12 )
                Electronic Location Identifier: e2020GH000305
                Affiliations
                [ 1 ] Center for Monsoon System Research, Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China
                [ 2 ] University of Chinese Academy of Sciences Beijing China
                [ 3 ] School of Atmospheric Sciences Sun Yat‐sen University Zhuhai China
                Author notes
                Author information
                https://orcid.org/0000-0001-9299-2729
                https://orcid.org/0000-0001-9327-9079
                Article
                Publisher ID: GH2204 Other ID: 2020GH000305
                DOI: 10.1029/2020GH000305
                PMC ID: 7742201
                PubMed ID: 33344871
                SO-VID: 2d8833e1-34fb-415a-8b8a-48bb8458c946
                Copyright © ©2020. The Authors.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 29 July 2020
                Date revision received : 30 October 2020
                Date accepted : 24 November 2020
                Page count
                Figures: 5, Tables: 0, Pages: 10, Words: 4447
                Funding
                Funded by: Key Research Program of Frontier Sciences, CAS
                Award ID: QYZDY‐SSW‐DQC024
                Funded by: Ministry of Science and Technology of China , open-funder-registry 10.13039/501100018537;
                Award ID: 2016YFA0600604
                Funded by: National Natural Science Foundation of China , open-funder-registry 10.13039/501100001809;
                Award ID: 41950410756
                Award ID: 41675061
                Categories
                Subject: The COVID‐19 Pandemic: Linking Health, Society and Environment
                Subject: Geohealth
                Subject: Impacts of Climate Change: Human Health
                Subject: Public Health
                Subject: Atmospheric Composition and Structure
                Subject: Pollution: Urban and Regional
                Subject: Aerosols and Particles
                Subject: Biogeosciences
                Subject: Pollution: Urban, Regional and Global
                Subject: Oceanography: General
                Subject: Marine Pollution
                Subject: Natural Hazards
                Subject: Megacities and Urban Environment
                Subject: Research Article
                Subject: Research Articles
                Custom metadata
                source-schema-version-number 2.0
                cover-date December 2020
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.5 mode:remove_FC converted:16.12.2020

                Keywords: climate change and extremes,covid‐19,india,population density,temperature and humidity
                Data availability:
                Keywords: climate change and extremes, covid‐19, india, population density, temperature and humidity

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