Background The COVID-19 pandemic has had a profound global impact on governments, health care systems, economies, and populations around the world. Within the East Asia and Pacific region, some countries have mitigated the spread of the novel coronavirus effectively and largely avoided severe negative consequences, while others still struggle with containment. As the second wave reaches East Asia and the Pacific, it becomes more evident that additional SARS-CoV-2 surveillance is needed to track recent shifts, rates of increase, and persistence associated with the pandemic. Objective The goal of this study is to provide advanced surveillance metrics for COVID-19 transmission that account for speed, acceleration, jerk, persistence, and weekly shifts, to better understand country risk for explosive growth and those countries who are managing the pandemic successfully. Existing surveillance coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until an effective vaccine is developed. We provide novel indicators to measure disease transmission. Methods Using a longitudinal trend analysis study design, we extracted 330 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in East Asia and the Pacific as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. Results The standard surveillance metrics for Indonesia, the Philippines, and Myanmar were concerning as they had the largest new caseloads at 4301, 2588, and 1387, respectively. When looking at the acceleration of new COVID-19 infections, we found that French Polynesia, Malaysia, and the Philippines had rates at 3.17, 0.22, and 0.06 per 100,000. These three countries also ranked highest in terms of jerk at 15.45, 0.10, and 0.04, respectively. Conclusions Two of the most populous countries in East Asia and the Pacific, Indonesia and the Philippines, have alarming surveillance metrics. These two countries rank highest in new infections in the region. The highest rates of speed, acceleration, and positive upwards jerk belong to French Polynesia, Malaysia, and the Philippines, and may result in explosive growth. While all countries in East Asia and the Pacific need to be cautious about reopening their countries since outbreaks are likely to occur in the second wave of COVID-19, the country of greatest concern is the Philippines. Based on standard and enhanced surveillance, the Philippines has not gained control of the COVID-19 epidemic, which is particularly troubling because the country ranks 4th in population in the region. Without extreme and rigid social distancing, quarantines, hygiene, and masking to reverse trends, the Philippines will remain on the global top 5 list of worst COVID-19 outbreaks resulting in high morbidity and mortality. The second wave will only exacerbate existing conditions and increase COVID-19 transmissions.

Social media (SoMe) offers great potential to expand access to health information, but a significant proportion of users consume its content instead of consulting a physician. We sought to quantify the volume and characterize the accuracy of men’s health-related content on TikTok and Instagram. We searched TikTok and Instagram for the terms: testosterone, erectile dysfunction, male infertility, semen retention, Peyronie’s disease, and vasectomy. The top 10 hashtags for each term were used to estimate the total impressions for each term on each platform, and posts were then characterized by creator type, content type, and accuracy (1 to 5 scale). TikTok had 2,312,407,100 impressions and Instagram had 3,107,300 posts across all topics. Semen retention had the most impressions on TikTok (1,216,074,000) and posts on Instagram (1,077,000). Physicians created only a small portion of total TikTok and Instagram posts (10.3% and 12.9%, respectively). Across all topics, the accuracy of content was poor (2.6 ± 1.7), however, physician posts were more accurate than non-physician posts (mean 4.2 ± 1.2 vs 2.3 ± 1.6, p < 0.001, respectively). Men’s health content is popular on TikTok and Instagram but is not accurate. We recommend that physicians actively engage in SoMe to address misinformation.

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Purpose To develop nomograms that predict the detection of clinically significant prostate cancer at diagnostic biopsy based on multiparametric prostate MRI (mpMRI), serum biomarkers, and patient clinicodemographic features. Materials and Methods Nomograms were developed from a cohort of biopsy-naïve men presenting to our 11-hospital system with a PSA of 2-20ng/mL who underwent pre-biopsy mpMRI from March 2018-June 2021 (n = 1494). The outcomes were the presence of clinically significant and high-grade prostate cancer (defined as ≥ GG2 [Grade Group 2] and ≥ GG3 prostate cancer, respectively). Using significant variables on multivariable logistic regression, individual nomograms were developed for men with PSA, % free PSA, or prostate health index (PHI) when available. The nomograms were both internally validated and evaluated in an independent cohort of 366 men presenting to our hospital system from July 2021-February 2022. Results 1031 of 1494 men (69%) underwent biopsy after initial evaluation with mpMRI, 493 (47.8%) of whom were found to have ≥ GG2 PCa, and 271 (26.3%) were found to have ≥ GG3 PCa. Age, race, highest PIRADS score, prostate health index (PHI) when available, % free PSA when available, and PSA density were significant predictors of ≥ GG2 and ≥ GG3 PCa on multivariable analysis and were used for nomogram generation. Accuracy of nomograms in both the training cohort and independent cohort were high, with areas under the curves (AUC) of ≥ 0.885 in the training cohort and ≥ 0.896 in the independent validation cohort. In our independent validation cohort, our model for ≥ GG2 prostate cancer with PHI saved 39.1% of biopsies (143/366) while only missing 0.8% of csPCa (1/124) with a biopsy threshold of 20% probability of csPCa. Conclusions Here we developed nomograms combining serum testing and mpMRI to help clinicians risk stratify patients with elevated PSA of 2-20ng/mL who are being considered for biopsy. Our nomograms are available at https://rossnm1.shinyapps.io/MynMRIskCalculator/ to aid with biopsy decisions.

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