Effects of temperature on COVID-19 transmission

Pawar, Shrikant; Stanam, Aditya; Chaudhari, Mamata; Rayudu, Durga

doi:10.1101/2020.03.29.20044461

Cited by 33 publications

(35 citation statements)

References 4 publications

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“…As for other viruses, temperature and humidity seem to be factors with some influence on the spread of SARS-CoV-2, but recent studies led to contrasting results. In general, a negative relationship is found between air temperature and the spread of SARS-CoV-2 virus 13,14 , but a positive one 15 and a lack of effect 16 have also been reported. In the case of humidity, limited 17,18 , positive 19 and negative 13 effects on the infection rate have been reported.…”

Section: Introductionmentioning

confidence: 97%

Climatic factors influence COVID-19 outbreak as revealed by worldwide mortality

Quilodrán

Currat

Montoya‐Burgos

2020

Preprint

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The COVID-19 outbreak is triggering a global crisis that is challenging governments, health systems and the scientific community worldwide 1 . A central question in the pandemic is whether climatic factors modulate its progression. This information is key to epidemiologists and healthcare decision-makers for improving their management plans 2 .Previous attempts to assess the impact of climatic parameters have yielded ambiguous results, either because they were using geographically or temporally restricted data, or because they were comparing infection rates across countries, which were measured differently depending on local screening strategies. In March 2020, the spread of COVID-19 dramatically increased the number of countries recording deaths 3 , providing an opportunity to use mortality rate, which is measured more homogeneously across countries than infection rates, as a descriptor of the COVID-19 outbreak over a large latitudinal range. Here, using data recorded in 208 territories from 88 countries, we show that mortality rate is negatively influenced by warmer air temperature and positively affected by higher relative humidity. Each additional Celsius degree decreases mortality rate by ~4%, while a 1% increase in relative humidity raises . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) : medRxiv preprint mortality rate by ~2%. Temperature is positively correlated with UV-index, for which one unit of increase results in a ~15% decrease in the mortality rate. We also show that other factors contribute to the dynamics of the COVID-19 outbreak, such as the proportion of vulnerable age classes in the population, access to a non-overwhelmed health system, as well as governmental travel restrictions for controlling the spread of the disease. All of them are critical factors impacting the mortality rate of COVID-19. The influence of climatic factors is a warning to all southern hemisphere countries where winter is coming soon. Northern hemisphere countries should also be warned that climatic factors alone will likely not be sufficient to contain the disease.

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Section: Introductionmentioning

confidence: 97%

Climatic factors influence COVID-19 outbreak as revealed by worldwide mortality

Quilodrán

Currat

Montoya‐Burgos

2020

Preprint

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“…Clustering E is based on temperature pro le only and it clearly suggested that higher temperature produced higher R 0 . This is a unique nding in itself as the role of temperature in the spread of COVID-19 has been studied [15][16][17][18][19][20][21][22] and the predominant prediction was mostly the opposite; evidence from published studies documented negative associations between increasing temperature and COVID-19 transmission 15,17,22 .…”

Section: Discussionmentioning

confidence: 99%

“…Control effort proved one of the keys to prevent and contain the spatial spread 14 . The role of temperature in the spread of COVID-19 has been studied [15][16][17][18][19][20][21][22] and debated among policymakers.…”

Section: Introductionmentioning

confidence: 99%

COVID-19 in China: Risk Factors and R0 Revisited

Khan

Zhang

Zafar

et al. 2020

Preprint

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Abstract Background: The COVID-19 epidemic had spread rapidly through China and subsequently has proliferated globally leading to a pandemic situation around the globe. Human-to-human transmissions, as well as asymptomatic transmissions of the infection, have been confirmed. As of April 3rd, public health crisis in China due to COVID-19 is potentially under control. Methods: We compiled a daily dataset of case counts, mortality, recovery, temperature, population density, and demographic information for each prefecture during the period of January 11 to April 07, 2020 (excluding Wuhan from our analysis due to missing data). Understanding the characteristics of spatiotemporal clustering of the COVID-19 epidemic and R0 is critical in effectively preventing and controlling the ongoing global pandemic. The prefectures were grouped based on several relevant features using unsupervised machine learning techniques. We performed a computational analysis utilizing the reported cases in China to estimate the revised R0 among different regions for prevention planning in an ongoing global pandemic. Results: Finally, our results indicate that the impact of temperature and demographic (different age group percentage compared to the total population) factors on virus transmission may be characterized using a stochastic transmission model. Conclusions: Such predictions will help prioritize segments of a given community/ region for action and provide a visual aid in designing prevention strategies for a specific geographic region. Furthermore, revised estimation and our methodology will aid in improving the human health consequences of COVID-19 elsewhere.

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“…We recognize that material supplies from the outside might be essential to the region's survival. To minimize risk, a consignment loaded into a truck outside the region should be kept inside the truck for 2-3 days, which is the estimated lifetime of the virus on surfaces [18,22]. Only thereafter should it be delivered to the virus-free region.…”

Section: §0 Introductionmentioning

confidence: 99%

“…Another factor which probably works in our favour is that summer is just arriving or has already arrived in most of the affected regions. There is some evidence [22,26] to indicate that the transmissibility of the virus is reduced in summer. The initial outbreak in Australia and New Zealand, which were in summer when the virus first arrived, has remained quite muted.…”

Section: §0 Introductionmentioning

confidence: 99%

Self-Burnout – A New Path to the End of COVID-19

Shayak

Rand

2020

Preprint

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In this work we use mathematical modeling to describe one possible route to the end of COVID-19, which does not feature either vaccination or herd immunity. We consider a region where the following conditions hold true : (a) there is no influx of cases from the outside, (b) there is extensive social distancing, though not necessarily a full lockdown, so that mass transmission events do not occur, and (c) testing capacity is high relative to the actual number of new cases per day. These conditions can make it possible for the region to initiate the endgame phase of epidemic management, wherein the virus is slowly starved of new targets through a combination of social distancing, sanitization, contact tracing and extensive testing. The dynamics of the cases in this regime is governed by a single-variable first order linear delay differential equation, whose stability criterion can be obtained explicitly. Analysis of the equation can tell us which social restrictions may be relaxed during the endgame, and which may not. For example, in an academic institution, a small research group might be allowed to meet in person once a week while classroom instruction should remain fully suspended. If the endgame can be played out for a long enough time, we claim that the disease can eventually get completely contained without affecting a significant fraction of the region's population. We present estimates of the duration for which the epidemic is expected to last, finding an interval of approximately 5-15 weeks after the endgame strategy is initiated.

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Effects of temperature on COVID-19 transmission

Cited by 33 publications

References 4 publications

Climatic factors influence COVID-19 outbreak as revealed by worldwide mortality

Climatic factors influence COVID-19 outbreak as revealed by worldwide mortality

COVID-19 in China: Risk Factors and R0 Revisited

Self-Burnout – A New Path to the End of COVID-19

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