Influence of population density, temperature, and absolute humidity on spread and decay durations of COVID-19: A comparative study of scenarios in China, England, Germany, and Japan.
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ABSTRACT:
SUBMITTER: Diao Y
PROVIDER: S-EPMC7736723 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe with about 2.2 million confirmed cases and more than 150,000 deaths as of April 17, 2020. In this work, mathematical models are used to reproduce data of the early evolution of the COVID-19 outbreak in Germany, taking into account the effect of actual and hypothetical non-pharmaceutical interventions. Systems of differential equations of SEIR type are extended to account for undetected infections, stages of infection, and age groups. The models are calibrated on data until April 5. Data from April 6 to 14 are used for model validation. We simulate different possible strategies for the mitigation of the current outbreak, slowing down the spread of the virus and thus reducing the peak in daily diagnosed cases, the demand for hospitalization or intensive care units admissions, and eventually the number of fatalities. Our results suggest that a partial (and gradual) lifting of introduced control measures could soon be possible if accompanied by further increased testing activity, strict isolation of detected cases, and reduced contact to risk groups.
| S-EPMC7473552 | biostudies-literature
Project description:Seasonal influenza epidemics are associated with various meteorological factors. Recently absolute humidity (AH) has garnered attention, and some epidemiological studies show an association between AH and human influenza infection. However, they mainly analyzed weekly surveillance data, and daily data remains largely unexplored despite its potential benefits. In this study, we analyze daily influenza surveillance data using a distributed lag non-linear model to examine the association of AH with the number of influenza cases and the magnitude of the association. Additionally, we investigate how adjustment for seasonality and autocorrelation in the model affect results. All models used in the study showed a significant increase in the number of influenza cases as AH decreased, although the magnitude of the association differed substantially by model. Furthermore, we found that relative risk reached a peak at lag 10-14 with extremely low AH. To verify these findings, further analysis should be conducted using data from other locations.
| S-EPMC7211015 | biostudies-literature
Project description:Experimental and epidemiologic evidence indicates that variations of absolute humidity account for the onset and seasonal cycle of epidemic influenza in temperate regions. A role for absolute humidity in the transmission of pandemic influenza, such as 2009 A/H1N1, has yet to be demonstrated and, indeed, outbreaks of pandemic influenza during more humid spring, summer, and autumn months might appear to constitute evidence against an effect of humidity. However, here the authors show that variations of the basic and effective reproductive numbers for influenza, caused by seasonal changes in absolute humidity, are consistent with the general timing of pandemic influenza outbreaks observed for 2009 A/H1N1 in temperate regions, as well as wintertime transmission of epidemic influenza. Indeed, absolute humidity conditions correctly identify the region of the United States vulnerable to a third, wintertime wave of pandemic influenza. These findings suggest that the timing of pandemic influenza outbreaks is controlled by a combination of absolute humidity conditions, levels of susceptibility, and changes in population-mixing and contact rates.
| S-EPMC3011950 | biostudies-literature
Project description:BackgroundSARS-CoV-2 caused the COVID-19 pandemic in 2020. The virus is likely to show seasonal dynamics in European climates as other respiratory viruses and coronaviruses do. Analysing the association with meteorological factors might be helpful to anticipate how cases will develop with changing seasons.MethodsRoutinely measured ambient daily mean temperature, absolute humidity, and relative humidity were the explanatory variables of this analysis. Test-positive COVID-19 cases represented the outcome variable. The analysis included 54 English cities. A two-stage meta-regression was conducted. At the first stage, we used a quasi-Poisson generalized linear model including distributed lag non-linear elements. Thereby, we investigate the explanatory variables' non-linear effects as well as the non-linear effects across lags.ResultsThis study found a non-linear association of COVID-19 cases with temperature. At 11.9°C there was 1.62-times (95%-CI: 1.44; 1.81) the risk of cases compared to the temperature-level with the smallest risk (21.8°C). Absolute humidity exhibited a 1.61-times (95%-CI: 1.41; 1.83) elevated risk at 6.6 g/m3 compared to the centering at 15.1 g/m3. When adjusting for temperature RH shows a 1.41-fold increase in risk of COVID-19 incidence (95%-CI: 1.09; 1.81) at 60.7% in respect to 87.6%.ConclusionThe analysis suggests that in England meteorological variables likely influence COVID-19 case development. These results reinforce the importance of non-pharmaceutical interventions (e.g., social distancing and mask use) during all seasons, especially with cold and dry weather conditions.
| S-EPMC7935674 | biostudies-literature
Project description:BACKGROUND:The UK government introduced social distancing measures between 16-22 March 2020, aiming to slow down transmission of COVID-19. AIM:To explore the spreading of COVID-19 in relation to population density after the introduction of social distancing measures. DESIGN & SETTING:Longitudinal design with 5-weekly COVID-19 incidence rates per 100 000 people for 149 English Upper Tier Local Authorities (UTLAs), between 16 March and 19 April 2020. METHOD:Multivariable multilevel model to analyse weekly incidence rates per 100 000 people; time was level-1 unit and UTLA level-2 unit. Population density was divided into quartiles. The model included an interaction between week and population density. Potential confounders were percentage aged ?65, percentage non-white British, and percentage in two highest classes of the National Statistics Socioeconomic Classification. Co-variates were male life expectancy at birth, and COVID-19 prevalence rate per 100 000 people on March 15. Confounders and co-variates were standardised around the mean. RESULTS:Incidence rates per 100 000 people peaked in the week of March 30-April 5, showing higher adjusted incidence rate per 100 000 people (46.2; 95% confidence interval [CI] = 40.6 to 51.8) in most densely populated ULTAs (quartile 4) than in less densely populated ULTAs (quartile 1: 33.3, 95% CI = 27.4 to 37.2; quartile 2: 35.9, 95% CI = 31.6 to 40.1). Thereafter, incidence rate dropped in the most densely populated ULTAs resulting in rate of 22.4 (95% CI = 16.9 to 28.0) in the week of April 13-19; this was lower than in quartiles 1, 2, and 3, respectively 31.4 (95% CI = 26.5 to 36.3), 34.2 (95% CI = 29.9 to 38.5), and 43.2 (95% CI = 39.0 to 47.4). CONCLUSION:After the introduction of social distancing measures, the incidence rates per 100 000 people dropped stronger in most densely populated ULTAs.
| S-EPMC7465584 | biostudies-literature
Project description:Norovirus (NoV) is one of the main causative agents of acute gastroenteritis worldwide. In temperate climates, outbreaks peak during the winter season. The mechanism by which climatic factors influence the occurrence of NoV outbreaks is unknown. We hypothesized that humidity is linked to NoV seasonality. Human NoV is not cultivatable, so we used cultivatable murine norovirus (MNV) as a surrogate to study its persistence when exposed to various levels of relative humidity (RH) from low (10% RH) to saturated (100% RH) conditions at 9 and 25°C. In addition, we conducted similar experiments with virus-like particles (VLPs) from the predominant GII-4 norovirus and studied changes in binding patterns to A, B, and O group carbohydrates that might reflect capsid alterations. The responses of MNV and VLP to humidity were somewhat similar, with 10 and 100% RH exhibiting a strong conserving effect for both models, whereas 50% RH was detrimental for MNV infectivity and VLP binding capacity. The data analysis suggested that absolute humidity (AH) rather than RH is the critical factor for keeping NoV infectious, with an AH below 0.007 kg water/kg air being favorable to NoV survival. Retrospective surveys of the meteorological data in Paris for the last 14 years showed that AH average values have almost always been below 0.007 kg water/kg air during the winter (i.e., 0.0046 ± 0.0014 kg water/kg air), and this finding supports the fact that low AH provides an ideal condition for NoV persistence and transmission during cold months.
| S-EPMC4249182 | biostudies-literature
Project description:Much of the observed wintertime increase of mortality in temperate regions is attributed to seasonal influenza. A recent reanalysis of laboratory experiments indicates that absolute humidity strongly modulates the airborne survival and transmission of the influenza virus. Here, we extend these findings to the human population level, showing that the onset of increased wintertime influenza-related mortality in the United States is associated with anomalously low absolute humidity levels during the prior weeks. We then use an epidemiological model, in which observed absolute humidity conditions temper influenza transmission rates, to successfully simulate the seasonal cycle of observed influenza-related mortality. The model results indicate that direct modulation of influenza transmissibility by absolute humidity alone is sufficient to produce this observed seasonality. These findings provide epidemiological support for the hypothesis that absolute humidity drives seasonal variations of influenza transmission in temperate regions.
| S-EPMC2826374 | biostudies-literature
Project description:BackgroundThe impact of climate change on mental health largely remains to be evaluated. Although growing evidence has reported a short-term association between suicide and temperature, future projections of temperature-attributable suicide have not been thoroughly examined.ObjectivesWe aimed to project the excess temperature-related suicide mortality in Japan under three climate change scenarios until the 2090s.MethodsDaily time series of mean temperature and the number of suicide deaths in 1973-2015 were collected for 47 prefectures in Japan. A two-stage time-stratified case-crossover analysis was used to estimate the temperature-suicide association. We obtained the modeled daily temperature series using five general circulation models under three climate change scenarios from the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathways scenarios (SSPs): SSP1-2.6, SSP2-4.5, and SSP5-8.5. We projected the excess temperature-related suicide mortality until 2099 for each scenario and evaluated the net relative changes compared with the 2010s.ResultsDuring 1973-2015, there was a total of 1,049,592 suicides in Japan. Net increases in temperature-related excess suicide mortality were estimated under all scenarios. The net change in 2090-2099 compared with 2010-2019 was 1.3% [95% empirical confidence interval (eCI): 0.6, 2.4] for the intermediate-emission scenario (SSP2-4.5), 0.6% (95% eCI: 0.1, 1.6) for a low-emission scenario (SSP1-2.6), and 2.4% (95% eCI: 0.7, 3.9) for the extreme scenario (SSP5-8.5). The increases were greater the more extreme the scenarios were, with the highest increase under the most extreme scenario (SSP5-8.5).DiscussionThis study indicates that Japan may experience a net increase in excess temperature-related suicide mortality, especially under the intermediate and extreme scenarios. The findings underscore the importance of mitigation policies. Further investigations of the future impacts of climate change on mental health including suicide are warranted. https://doi.org/10.1289/EHP11246.
| S-EPMC10666824 | biostudies-literature
Project description:This paper examines issues related to the future supply of registered nursing staff, midwives and health visitors in the National Health Service (NHS) in England at a time when there are major public sector funding constraints and as more of these staff are reaching retirement age. Based on available workforce data, the paper reviews different possible scenarios for the supply of NHS nurses over a ten year period, assessing the impact of different numbers of new staff being trained and of varying retirement patterns from the ageing profession.The government in England has more policy levers available than is the case in many other countries. It determines the number of pre-registration training places that are commissioned and funded, it is the major employer, and it also controls the inflow of nurses from other countries through migration policies. Scenario models provide a picture of what the future might look like under various assumptions. These outcomes can be quantified and the results used to assess the risks and opportunities of alternate policy decisions. The approach used in this paper is that of the aggregate deterministic supply model.As part of this exercise, eight scenarios were selected and modelled. These were:A. "No change"- current inflows and outflowsB. "Redundancies" - current inflow with higher outflowC. "Improved retention" - current inflow with lower outflowD. "Reduced training intakes A" - lower inflows with lower outflowE. "Reduced training intakes B" - lower inflow with higher outflowsF. "Pension time-bomb"- current inflow with a higher rate of retirementG. "Pension delayed"- current inflow with a lower rate of retirementH. "Worst case" - lower inflow and higher outflow including higher retirementMost of the scenarios indicate that a reduction in the supply of nursing staff to NHS England is possible over the next ten years. Small changes in assumptions can make a substantial difference to outcomes and therefore emphasize the point that it is unwise to base policy decisions on a single projection. It is important that different scenarios are considered that may be regarded as possible futures, based on a realistic assessment of the available workforce data, policies and broader labour market and funding outlook.
| S-EPMC3459709 | biostudies-literature
Project description:BACKGROUND:Faced with the global pandemic of COVID-19, declared by World Health Organization (WHO) on March 11th 2020, and the need to better understand the seasonal behavior of the virus, our team conducted this systematic review to describe current knowledge about the emergence and replicability of the virus and its connection with different weather factors such as temperature and relative humidity. METHODS:The review was registered with the PROSPERO database. The electronic databases PubMed, Scopus, Web of Science, Cochrane Library, LILACS, OpenGrey and Google Scholar were examined with the searches restricted to the years 2019 and 2020. Risk of bias assessment was performed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist tool. The GRADE tool was used to assess the certainty of the evidence. RESULTS:The initial screening identified 517 articles. After examination of the full texts, seventeen studies met the review's eligibility criteria. Great homogeneity was observed in the findings regarding the effect of temperature and humidity on the seasonal viability and transmissibility of COVID-19. Cold and dry conditions were potentiating factors on the spread of the virus. After quality assessment, two studies had a high risk of bias, eleven studies were scored as moderate risk of bias, and four studies were classified as low risk of bias. The certainty of evidence was graded as low for both outcomes evaluated. CONCLUSION:Considering the existing scientific evidence, warm and wet climates seem to reduce the spread of COVID-19. However, these variables alone could not explain most of the variability in disease transmission. Therefore, the countries most affected by the disease should focus on health policies, even with climates less favorable to the virus. Although the certainty of the evidence generated was classified as low, there was homogeneity between the results reported by the included studies.
| S-EPMC7500589 | biostudies-literature