An open repository of real-time COVID-19 indicators.

The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: Operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from deidentified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data are available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making.

Correction: Prevalence of polypharmacy and the association with non-communicable diseases in Qatari elderly patients attending primary healthcare centers: A cross-sectional study.

[This corrects the article DOI: 10.1371/journal.pone.0234386.].

Prevalence of polypharmacy and the association with non-communicable diseases in Qatari elderly patients attending primary healthcare centers: A cross-sectional study.

BACKGROUND: Polypharmacy has become a global public health concern particularly in the elderly population. The elderly population is the most susceptible to the negative effects of polypharmacy due to their altered pharmacokinetics and decreased drug clearance. Therefore, polypharmacy can lead to poor health status and higher rates of morbidity and mortality. OBJECTIVE: The objective of this study was to determine the prevalence of polypharmacy (≥ 5 drugs) and its association with non-communicable diseases (NCDs) in elderly (≥65 years) Qatari patients attending Primary Healthcare (PHC) centers in Qatar. METHODS: A retrospective cross-sectional analysis was conducted using the Electronic Medical Record (EMR) database of all PHC centers in Qatar for six months (April-September 2017). RESULTS: Out of 5639 patients screened, 75.5% (95% CI: 74.3-76.6) were exposed to polypharmacy. Females were 1.18 times more likely to have polypharmacy compared to males (95% CI: 1.03-1.34). The multivariate analysis identified having hypertension (AOR 1.71; 95% CI: 1.38-2.13), diabetes (AOR 2.38; 95% CI: 1.97-2.87), dyslipidemia (AOR 1.29; 95% CI: 1.06-1.56), cardiovascular disease (AOR 1.56; 95% CI: 1.25-1.95) and asthma (AOR 1.39; 95% CI: 1.13-1.72) to be independent parameters associated with polypharmacy. Also, the Body Mass Index (BMI) and number of NCDs were found to be significant independent parameters associated with polypharmacy. CONCLUSIONS: The prevalence of polypharmacy among Qatari elderly attending PHC Centers is very high. Our findings confirm the strong relationship between polypharmacy and BMI, and certain NCDs. Healthcare professionals should be educated about the magnitude of polypharmacy, its negative effects, and its associated factors. Best practice guidelines should be developed for improved medical practice in the prescription of medications for such a vulnerable population.