Evaluating temperature and humidity gradients of COVID-19 infection rates in light of Non-Pharmaceutical Interventions
Choma, J.; Mellado, B.; Lieberman, B.; Correa, F.; Maslo, C.; Naude, J.; Ruan, X.; Hayashi, K.; Monnakgotla, K.; Dahbi, S.-E.; Stevenson, F. D.
Show abstract
We evaluate potential temperature and humidity impact on the infection rate of COVID-19 with a data up to June 10th 2020, which comprises a large geographical footprint. It is critical to analyse data from different countries or regions at similar stages of the pandemic in order to avoid picking up false gradients. The degree of severity of NPIs is found to be a good gauge of the stage of the pandemic for individual countries. Data points are classified according to the stringency index of the NPIs in order to ensure that comparisons between countries are made on equal footing. We find that temperature and relative humidity gradients dont significantly deviate from the zero-gradient hypothesis. Upper limits on the absolute value of the gradients are set. The procedure chosen here yields 6 10-3 {degrees}C-1 and 3.3 10-3 (%)-1 upper limits on the absolute values of the temperature and relative humidity gradients, respectively, with a 95% Confidence Level. These findings do not preclude existence of seasonal effects and are indicative that these are likely to be nuanced.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Uncertainty and Inconsistency of COVID-19 Non-Pharmaceutical Intervention Effects with Multiple Competitive Statistical Models 95%
- Pareto-based evaluation of national responses to COVID-19 pandemic shows that saving lives and protecting economy are non-trade-off objectives 94%
- Easing COVID-19 lockdown measures while protecting the older restricts the deaths to the level of the full lockdown 94%
Similar papers in this journal
- Tracking the Dynamics and Allocating Tests for COVID-19 in Real-Time: an Acceleration Index with an Application to French Age Groups and Départements * 95%
- SARS-CoV-2 infection dynamics in Denmark, February through October 2020: Nature of the past epidemic and how it may develop in the future 94%
- On the use of growth models for forecasting epidemic outbreaks with application to COVID-19 data 94%
Similar papers in this journal
- A semi-parametric, state-space compartmental model with time-dependent parameters for forecasting COVID-19 cases, hospitalizations, and deaths 93%
- Time-aggregated mobile phone mobility data are sufficient for modelling influenza spread: the case of Bangladesh 93%
- Computationally efficient framework for diagnosing, understanding, and predicting biphasic population growth 92%
Similar papers in this journal
- Nowcasting and Forecasting COVID-19 Waves: The Recursive and Stochastic Nature of Transmission 93%
- Assessing the impact of widespread respirator use in curtailing COVID-19 transmission in the United States 93%
- Sensitivity of endemic behaviour of Covid-19 under a multi-dose vaccination regime, to various biological parameters and control variables 92%
Similar papers in this journal
- The impact of policy timing on the spread of COVID-19 95%
- Estimate of the rate of unreported COVID-19 cases during the first outbreak in Rio de Janeiro 93%
- Estimating the size of the COVID-19 outbreak in Italy: Application of an exponential decay model to the weighted and cumulative average daily growth rate 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.