Book Review

[...]residents, fellows, and practicing pathologists will find this book very practical, educational, illustrative, and informative. The table of the updated, simplified AIH scoring system (2008) is also displayed. [...]staging is illustrated with representative photomicrographs and reference to the Ishak and Batts-Ludwig systems. [...]some of the links in the eBook are not accurately pointed to the appropriate location in the text. [...]the book is highly recommended for the readers who are interested in non-neoplastic liver pathology.

Associations of stay-at-home order and face-masking recommendation with trends in daily new cases and deaths of laboratory-confirmed COVID-19 in the United States

BACKGROUND AND OBJECTIVES: Public health interventions were associated with reduction in coronavirus disease 2019 (COVID-19) transmission in China, but their impacts on COVID-19 epidemiology in other countries are unclear. We examined the associations of stay-at-home order (SAHO) and face-masking recommendation with epidemiology of laboratory-confirmed COVID-19 in the United States. METHODS: In this quasi-experimental study, we modeled the temporal trends in daily new cases and deaths of COVID-19, and COVID-19 time-varying reproduction numbers (Rt) in the United States between March 1 and April 20, 2020, and conducted simulation studies. RESULTS: The number and proportion of U.S. residents under SAHO increased between March 19 and April 7, and plateaued at 29,0829,980 and 88.6%, respectively. Trends in COVID-19 daily cases and Rt reduced after March 23 (P<0.001) and further reduced on April 3 (P<0.001), which was associated with implementation of SAHO by 10 states on March 23, and face-masking recommendation on April 3, respectively. The estimates of Rt eventually fell below/around 1.0 on April 13. Similar turning points were identified in the trends of daily deaths with a lag time. Early implementation and early-removal of SAHO would be associated with significantly reduced and increased daily new cases and deaths, respectively.

Associations of Stay-at-Home Order and Face-Masking Recommendation with Trends in Daily New Cases and Deaths of Laboratory-Confirmed COVID-19 in the United States.

BACKGROUND AND OBJECTIVES: Public health interventions have reduced coronavirus disease 2019 (COVID-19) transmission in several countries, but their impacts on COVID-19 epidemics in the USA are unclear. We examined associations of stay-at-home order (SAHO) and face-masking recommendation with COVID-19 epidemics in the USA. METHODS: In this quasi-experimental interrupted time-series study, we modeled temporal trends in daily new cases and deaths of laboratory-confirmed COVID-19 cases, and COVID-19 time-varying reproduction numbers in the USA between March 1 and April 20, 2020. In addition, we conducted simulation analyses. RESULTS: The number of residents under SAHO increased since March 19 and plateaued at 290,829,980 (88.6% of the U.S. population) on April 7. Trends in COVID-19 time-varying reproduction numbers peaked on March 23, further reduced on April 3, and fell below/around 1.0 on April 13. Early-implementation and early-lift of SAHO would reduce and increase COVID-19 epidemics, respectively. Multivariable piecewise log-linear regression revealed the states' neighboring relationship with New York was linked to COVID-19 daily new cases and deaths. There were two turning points in daily new-case trend, being March 28 (slope-changes = -0.09) and April 3 (slope-changes = -0.09), which appeared to be associated with implementation of SAHO on March 28 (affecting 48.5% of the US population in 22 states and District of Columbia), and face-masking recommendation on April 3, respectively. There were also two turning points in daily new-death trend, being April 9 (slope-changes = -0.06) and April 19 (slope-changes = -0.90). CONCLUSIONS: We identified two turning points of COVID-19 daily new cases or deaths in the USA, which seem to be linked to implementation of SAHO and the Center for Disease Control's face-masking recommendation.

Associations of stay-at-home order and face-masking recommendation with trends in daily new cases and deaths of laboratory-confirmed COVID-19 in the United States.

BACKGROUND AND OBJECTIVES: Public health interventions were associated with reduction in coronavirus disease 2019 (COVID-19) transmission in China, but their impacts on COVID-19 epidemiology in other countries are unclear. We examined the associations of stay-at-home order (SAHO) and face-masking recommendation with epidemiology of laboratory-confirmed COVID-19 in the United States. METHODS: In this quasi-experimental study, we modeled the temporal trends in daily new cases and deaths of COVID-19, and COVID-19 time-varying reproduction numbers (Rt) in the United States between March 1 and April 20, 2020, and conducted simulation studies. RESULTS: The number and proportion of U.S. residents under SAHO increased between March 19 and April 7, and plateaued at 29,0829,980 and 88.6%, respectively. Trends in COVID-19 daily cases and Rt reduced after March 23 (P<0.001) and further reduced on April 3 (P<0.001), which was associated with implementation of SAHO by 10 states on March 23, and face-masking recommendation on April 3, respectively. The estimates of Rt eventually fell below/around 1.0 on April 13. Similar turning points were identified in the trends of daily deaths with a lag time. Early implementation and early-removal of SAHO would be associated with significantly reduced and increased daily new cases and deaths, respectively.

Trends and prediction in daily incidence of novel coronavirus infection in China, Hubei Province and Wuhan City: an application of Farr's law.

BACKGROUND: The recent outbreak of novel coronavirus (2019-nCoV) has infected tens of thousands of patients in China. Studies have forecasted future trends of the incidence of 2019-nCoV infection, but appeared unsuccessful. Farr's law is a classic epidemiology theory/practice for predicting epidemics. Therefore, we used and validated a model based on Farr's law to predict the daily-incidence of 2019-nCoV infection in China and 2 regions of high-incidence. METHODS: We extracted the 2019-nCoV incidence data of China, Hubei Province and Wuhan City from websites of the Chinese and Hubei health commissions. A model based on Farr's law was developed using the data available on Feb. 8, 2020, and used to predict daily-incidence of 2019-nCoV infection in China, Hubei Province and Wuhan City afterward. RESULTS: We observed 50,995 (37,001 on or before Feb. 8) incident cases in China from January 16 to February 15, 2020. The daily-incidence has peaked in China, Hubei Providence and Wuhan City, but with different downward slopes. If no major changes occur, our model shows that the daily-incidence of 2019-nCoV will drop to single-digit by February 25 for China and Hubei Province, but by March 8 for Wuhan city. However, predicted 75% confidence intervals of daily-incidence in all 3 regions of interest had an upward trend. The predicted trends overall match the prospectively-collected data, confirming usefulness of these models. CONCLUSIONS: This study shows the daily-incidence of 2019-nCoV in China, Hubei Province and Wuhan City has reached the peak and was decreasing. However, there is a possibility of upward trend.

Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model.

BACKGROUND AND OBJECTIVES: The daily incidence and deaths of coronavirus disease 2019 (COVID-19) in the USA are poorly understood. Internet search interest was found to be correlated with COVID-19 daily incidence in China, but has not yet been applied to the USA. Therefore, we examined the association of internet search-interest with COVID-19 daily incidence and deaths in the USA. METHODS: We extracted COVID-19 daily new cases and deaths in the USA from two population-based datasets, namely 1-point-3-acres.com and the Johns Hopkins COVID-19 data repository. The internet search-interest of COVID-19-related terms was obtained using Google Trends. The Pearson correlation test and general linear model were used to examine correlations and predict trends, respectively. RESULTS: There were 636,282 new cases and,325 deaths of COVID-19 in the USA from March 1 to April 15, 2020, with a crude mortality of 4.45%. The daily new cases peaked at 35,098 cases on April 10, 2020 and the daily deaths peaked at 2,494 on April 15, 2020. The search interest of COVID, "COVID pneumonia" and "COVID heart" were correlated with COVID-19 daily incidence, with 12 or 14 days of delay (Pearson's r = 0.978, 0.978 and 0.979, respectively) and deaths with 19 days of delay (Pearson's r = 0.963, 0.958 and 0.970, respectively). The 7-day follow-up with prospectively collected data showed no significant correlations of the observed data with the predicted daily new cases or daily deaths, using search interest of COVID, COVID heart, and COVID pneumonia. CONCLUSIONS: Search terms related to COVID-19 are highly correlated with the COVID-19 daily new cases and deaths in the USA.