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10.2196/18576 http://scihub22266oqcxt.onion/10.2196/18576 32319956!7187763!32319956     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       JMIR+Public+Health+Surveill 2020 ; 6 (2): e18576 Nephropedia Template TP {{tp|p=32319956|t=2020. Surveillance of COVID-19 in the General Population Using an Online Questionnaire: Report From 18,161 Respondents in China |pdf=|usr=}}{{32319956}} gab.com Text Surveillance of COVID-19 in the General Population Using an Online Questionnaire: Report From 18,161 Respondents in China JO: JMIR Public Health Surveill http://www.kidney.de/pget.php?&tw=1&pmid=32319956 #FOAvip BACKGROUND: The recent outbreak of the coronavirus disease (COVID-19) has become an international pandemic. So far, little is known about the role of an internet approach in COVID-19 participatory surveillance. OBJECTIVE: The aim of this study is to investigate whether an online survey can provide population-level information for observing prevalence trends during the early phase of an outbreak and identifying potential risk factors of COVID-19 infection. METHODS: A 10-item online questionnaire was developed according to medical guidelines and relevant publications. It was distributed between January 24 and February 17, 2020. The characteristics of respondents and temporal changes of various questionnaire-derived indicators were analyzed. RESULTS: A total of 18,161 questionnaires were returned, including 6.45% (n=1171) from Wuhan City. Geographical distributions of the respondents were consistent with the population per province (R(2)=0.61, P<.001). History of contact significantly decreased with time, both outside Wuhan City (R(2)=0.35, P=.002) and outside Hubei Province (R(2)=0.42, P<.001). The percentage of respondents reporting a fever peaked around February 8 (R(2)=0.57, P<.001) and increased with a history of contact in the areas outside Wuhan City (risk ratio 1.31, 95% CI 1.13-1.52, P<.001). Male sex, advanced age, and lung diseases were associated with a higher risk of fever in the general population with a history of contact. CONCLUSIONS: This study shows the usefulness of an online questionnaire for the surveillance of outbreaks like COVID-19 by providing information about trends of the disease and aiding the identification of potential risk factors. Twit Text FOAVip Surveillance of COVID-19 in the General Population Using an Online Questionnaire: Report From 18,161 Respondents in China ????JMIR Public Health Surveill http://www.kidney.de/pget.php?&tw=1&pmid=32319956 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32319956 #FOAvip English Wikipedia <ref>{{Cite pmid|32319956}}</ref> Surveillance of COVID-19 in the General Population Using an Online Questionnaire: Report From 18,161 Respondents in China #MMPMID32319956 Luo H; Lie Y; Prinzen FW JMIR Public Health Surveill 2020[Apr]; 6 (2): e18576 PMID32319956show ga BACKGROUND: The recent outbreak of the coronavirus disease (COVID-19) has become an international pandemic. So far, little is known about the role of an internet approach in COVID-19 participatory surveillance. OBJECTIVE: The aim of this study is to investigate whether an online survey can provide population-level information for observing prevalence trends during the early phase of an outbreak and identifying potential risk factors of COVID-19 infection. METHODS: A 10-item online questionnaire was developed according to medical guidelines and relevant publications. It was distributed between January 24 and February 17, 2020. The characteristics of respondents and temporal changes of various questionnaire-derived indicators were analyzed. RESULTS: A total of 18,161 questionnaires were returned, including 6.45% (n=1171) from Wuhan City. Geographical distributions of the respondents were consistent with the population per province (R(2)=0.61, P<.001). History of contact significantly decreased with time, both outside Wuhan City (R(2)=0.35, P=.002) and outside Hubei Province (R(2)=0.42, P<.001). The percentage of respondents reporting a fever peaked around February 8 (R(2)=0.57, P<.001) and increased with a history of contact in the areas outside Wuhan City (risk ratio 1.31, 95% CI 1.13-1.52, P<.001). Male sex, advanced age, and lung diseases were associated with a higher risk of fever in the general population with a history of contact. CONCLUSIONS: This study shows the usefulness of an online questionnaire for the surveillance of outbreaks like COVID-19 by providing information about trends of the disease and aiding the identification of potential risk factors. |*Coronavirus[MESH] |*Health Knowledge, Attitudes, Practice[MESH] |*Pandemics[MESH] |Adult[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Community-Based Participatory Research[MESH] |Coronavirus Infections/*epidemiology/prevention & control/*transmission[MESH] |Cough/etiology[MESH] |Disease Outbreaks/*prevention & control[MESH] |Female[MESH] |Fever/etiology[MESH] |Headache/etiology[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Pneumonia, Viral/*epidemiology/prevention & control/transmission[MESH] |Population Surveillance[MESH] |Prevalence[MESH]Surveillance of COVID-19 in the General Population Using an Online Que(epmc).pdf DeepDyve Pubget Overpricing