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10.1136/bmjopen-2021-049383 http://scihub22266oqcxt.onion/10.1136/bmjopen-2021-049383 35396278!8995577!35396278     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       BMJ+Open 2022 ; 12 (4): e049383 Nephropedia Template TP {{tp|p=35396278|t=2022. Impact of air temperature and containment measures on mitigating the intrahousehold transmission of SARS-CoV-2: a data-based modelling analysis |pdf=|usr=}}{{35396278}} gab.com Text Impact of air temperature and containment measures on mitigating the intrahousehold transmission of SARS-CoV-2: a data-based modelling analysis JO: BMJ Open http://www.kidney.de/pget.php?&tw=1&pmid=35396278 #FOAvip OBJECTIVES: Air temperature has been considered a modifiable and contributable variable in COVID-19 transmission. Implementation of non-pharmaceutical interventions (NPIs) has also made an impact on COVID-19 transmission, changing the transmission pattern to intrahousehold transmission under stringent containment measures. Therefore, it is necessary to re-estimate the influence of air temperature on COVID-19 transmission while excluding the influence of NPIs. DESIGN, SETTING AND PARTICIPANTS: This study is a data-based comprehensive modelling analysis. A stochastic epidemiological model, the ScEIQR model (contactable susceptible-exposed-infected-quarantined-removed), was established to evaluate the influence of air temperature and containment measures on the intrahousehold spread of COVID-19. Epidemic data on COVID-19, including daily confirmed cases, number of close contacts, etc, were collected from the National Health Commission of China. OUTCOME MEASURES: The model was fitted using the Metropolis-Hastings algorithm with a cost function based on the least squares method. The LOESS (locally weighted scatterplot smoothing) regression function was used to assess the relationship between air temperature and rate of COVID-19 transmission within the ScEIQR model. RESULTS: The ScEIQR model indicated that the optimal temperature for spread of COVID-19 peaked at 10? (50?), ranging from 5? to 14? (41?-57.2?). In the fitted model, the fitted intrahousehold transmission rate (beta') of COVID-19 was 10.22 (IQR 8.47-12.35) across mainland China. The association between air temperature and beta' of COVID-19 suggests that COVID-19 might be seasonal. Our model also validated the effectiveness of NPIs, demonstrating that diminishing contactable susceptibility (Sc) and avoiding delay in diagnosis and hospitalisation (eta) were more effective than contact tracing (kappa and rho). CONCLUSIONS: We constructed a novel epidemic model to estimate the effect of air temperature on COVID-19 transmission beyond implementation of NPIs, which can inform public health strategy and predict the transmission of COVID-19. Twit Text FOAVip Impact of air temperature and containment measures on mitigating the intrahousehold transmission of SARS-CoV-2: a data-based modelling analysis ????BMJ Open http://www.kidney.de/pget.php?&tw=1&pmid=35396278 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35396278 #FOAvip English Wikipedia <ref>{{Cite pmid|35396278}}</ref> Impact of air temperature and containment measures on mitigating the intrahousehold transmission of SARS-CoV-2: a data-based modelling analysis #MMPMID35396278 Liu D; Tai Q; Wang Y; Pu M; Zhang L; Su B BMJ Open 2022[Apr]; 12 (4): e049383 PMID35396278show ga OBJECTIVES: Air temperature has been considered a modifiable and contributable variable in COVID-19 transmission. Implementation of non-pharmaceutical interventions (NPIs) has also made an impact on COVID-19 transmission, changing the transmission pattern to intrahousehold transmission under stringent containment measures. Therefore, it is necessary to re-estimate the influence of air temperature on COVID-19 transmission while excluding the influence of NPIs. DESIGN, SETTING AND PARTICIPANTS: This study is a data-based comprehensive modelling analysis. A stochastic epidemiological model, the ScEIQR model (contactable susceptible-exposed-infected-quarantined-removed), was established to evaluate the influence of air temperature and containment measures on the intrahousehold spread of COVID-19. Epidemic data on COVID-19, including daily confirmed cases, number of close contacts, etc, were collected from the National Health Commission of China. OUTCOME MEASURES: The model was fitted using the Metropolis-Hastings algorithm with a cost function based on the least squares method. The LOESS (locally weighted scatterplot smoothing) regression function was used to assess the relationship between air temperature and rate of COVID-19 transmission within the ScEIQR model. RESULTS: The ScEIQR model indicated that the optimal temperature for spread of COVID-19 peaked at 10? (50?), ranging from 5? to 14? (41?-57.2?). In the fitted model, the fitted intrahousehold transmission rate (beta') of COVID-19 was 10.22 (IQR 8.47-12.35) across mainland China. The association between air temperature and beta' of COVID-19 suggests that COVID-19 might be seasonal. Our model also validated the effectiveness of NPIs, demonstrating that diminishing contactable susceptibility (Sc) and avoiding delay in diagnosis and hospitalisation (eta) were more effective than contact tracing (kappa and rho). CONCLUSIONS: We constructed a novel epidemic model to estimate the effect of air temperature on COVID-19 transmission beyond implementation of NPIs, which can inform public health strategy and predict the transmission of COVID-19. |*COVID-19/epidemiology/prevention & control[MESH] |*SARS-CoV-2[MESH] |Contact Tracing/methods[MESH] |Humans[MESH] |Quarantine[MESH]Impact of air temperature and containment measures on mitigating the (epmc).pdf DeepDyve Pubget Overpricing