Knowledge and attitude towards pregnancy-related issues of Zika virus infection among general practitioners in Indonesia

Abstract Background The aim of this study was to assess the knowledge and attitudes towards pregnancy-related issues of Zika virus (ZIKV) infection among general practitioners (GPs), a frontline healthcare worker group, in Indonesia. Methods A cross-sectional, online survey assessing knowledge and attitudes towards ZIKV infection on multiple-item scales was sent to GPs in the Sumatra and Java islands of Indonesia. The associations between independent factors and either knowledge or attitude were assessed with logistic regressions. The correlation and association between knowledge and attitude were estimated. Results We included 457 (53.7%) out of 850 responses in the analysis. Among these, 304 (66.5%) and 111 (24.2%) respondents had a good knowledge and attitude, respectively. No demographic, workplace, professional development, or experiential characteristics related to ZIKV infection were associated with knowledge. In the multivariate analysis, only contact experience was associated with attitude. There was a significant, positive correlation between knowledge and attitude scores. Conclusions Although knowledge of pregnancy-related complications of ZIKV infection is relatively high among GPs in Indonesia, more than 75% of them had a poor attitude towards pregnancy-related issues of Zika. Strategies for enhancing the capacity of GPs to develop positive attitudes and respond to ZIKV infection are needed.https://deepblue.lib.umich.edu/bitstream/2027.42/152124/1/12879_2019_Article_4297.pd

Knowledge and attitude towards pregnancy-related issues of Zika virus infection among general practitioners in Indonesia

Abstract Background The aim of this study was to assess the knowledge and attitudes towards pregnancy-related issues of Zika virus (ZIKV) infection among general practitioners (GPs), a frontline healthcare worker group, in Indonesia. Methods A cross-sectional, online survey assessing knowledge and attitudes towards ZIKV infection on multiple-item scales was sent to GPs in the Sumatra and Java islands of Indonesia. The associations between independent factors and either knowledge or attitude were assessed with logistic regressions. The correlation and association between knowledge and attitude were estimated. Results We included 457 (53.7%) out of 850 responses in the analysis. Among these, 304 (66.5%) and 111 (24.2%) respondents had a good knowledge and attitude, respectively. No demographic, workplace, professional development, or experiential characteristics related to ZIKV infection were associated with knowledge. In the multivariate analysis, only contact experience was associated with attitude. There was a significant, positive correlation between knowledge and attitude scores. Conclusions Although knowledge of pregnancy-related complications of ZIKV infection is relatively high among GPs in Indonesia, more than 75% of them had a poor attitude towards pregnancy-related issues of Zika. Strategies for enhancing the capacity of GPs to develop positive attitudes and respond to ZIKV infection are needed.https://deepblue.lib.umich.edu/bitstream/2027.42/152124/1/12879_2019_Article_4297.pd

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use