scholarly journals Public Health Interventions for COVID-19 Reduce Kawasaki Disease in Taiwan

Children ◽  
2021 ◽  
Vol 8 (8) ◽  
pp. 623
Author(s):  
Ya-Ling Yang ◽  
Ho-Chang Kuo
Keyword(s):  
Public Health ◽  
Kawasaki Disease ◽  
Case Series ◽  
Health Interventions ◽  
Chang Gung Memorial Hospital ◽  
Public Health Interventions ◽  
Early Screening ◽  
Retrospective Case ◽  
Airway Infections ◽  
Case Series Study

Background: Kawasaki disease (KD) is a syndrome of unknown cause that results in high fever and coronary vasculitis in children. The incidence of KD increased in Taiwan over the past few decades. Taiwanese government executed domains of early screening, effective methods for isolation or quarantine, and digital technologies for identifying potential cases for the early elimination strategy for coronavirus disease 2019 (COVID-19) and public health interventions for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or COVID-19 pandemic, leading to an effective reduction of the risk of airway infections in children. The purpose of this study is to analyze whether those public health interventions reduce the incidence of KD in 2020. Methods: Patients with KD who visited Chang Gung Memorial Hospital (CGMH) between 1 January, 2018, and 31 December, 2020 were included for trend analysis. This is a retrospective case series study conducted at the CGMH, which consists of a network of seven hospital branches equipped with more than 10,000 beds in different areas of Taiwan. Results: Compared with the 2018 and 2019 databases, the incidence of KD decreased significantly by 30% and 31%, respectively (p < 0.05) in 2020, when public health interventions were comprehensively implemented in Taiwan. This result shows that the incidence of KD decreased during the COVID-19 pandemic in Taiwan without change of the presentation KD (typical or incomplete) and percentage of IVIG resistance in 2020. Conclusion: As public health interventions were carried out for the SARS-CoV-2 pandemic, the incidence of KD was significantly reduced in Taiwan. Is KD a preventable disease?

scholarly journals Impact of Spanish Public Health Measures on Emergency Visits and COVID- 19 diagnosed cases during the pandemic in Madrid

2020 ◽  
Vol 33 (4) ◽  
pp. 274-277 ◽  
Author(s):  
Francisco Javier Martín-Sánchez ◽  
Adrián Valls Carbó ◽  
Amanda López Picado ◽  
Carmen Martínez-Valero ◽  
Juande D. Miranda ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Case Series ◽  
Case Definitions ◽  
Retrospective Case ◽  
Emergency Visits ◽  
Health Measures ◽  
Case Series Study ◽  
Test Criteria ◽  
Series Study

Introduction. Changes in Public Health recommendations may have changed the number of emergency visits and COVID-19 diagnosed cases in an Emergency Department in Madrid. Material and methods. This retrospective case series study included all consecutive patients in a tertiary and urban ED in Madrid from 1st to 31st March. The sample was divided: NonCOVID-19, Non-investigated COVID-19, Possible COVID-19, Probable COVID-19, Confirmed COVID-19. Differences between public health periods were tested by ANOVA for each cohort, and by ANCOVA including the number of PCR tests (%) as covariate. Results. A total of 7,163 (4,071 Non-COVID-19, 563 Non-investigated COVID-19, 870 Possible, 648 Probable and 1,011 Confirmed COVID-19) cases were included. Public Health measurements applied during each period showed a clear effect on the case proportion for the five cohorts. Conclusion. The variability of case definitions and diagnostic test criteria may have impact on the number of emergency visits and COVID-19 diagnosed cases in Emergency Department.

scholarly journals An analysis of COVID-19 clusters in India

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pooja Sengupta ◽  
Bhaswati Ganguli ◽  
Sugata SenRoy ◽  
Aditya Chatterjee
Keyword(s):  
Public Health ◽  
Cluster Analysis ◽  
Population Density ◽  
Case Studies ◽  
Compartment Model ◽  
Health Interventions ◽  
Disease Spread ◽  
Second Phase ◽  
Public Health Interventions ◽  
Homogeneous Groups

Abstract Background In this study we cluster the districts of India in terms of the spread of COVID-19 and related variables such as population density and the number of specialty hospitals. Simulation using a compartment model is used to provide insight into differences in response to public health interventions. Two case studies of interest from Nizamuddin and Dharavi provide contrasting pictures of the success in curbing spread. Methods A cluster analysis of the worst affected districts in India provides insight about the similarities between them. The effects of public health interventions in flattening the curve in their respective states is studied using the individual contact SEIQHRF model, a stochastic individual compartment model which simulates disease prevalence in the susceptible, infected, recovered and fatal compartments. Results The clustering of hotspot districts provide homogeneous groups that can be discriminated in terms of number of cases and related covariates. The cluster analysis reveal that the distribution of number of COVID-19 hospitals in the districts does not correlate with the distribution of confirmed COVID-19 cases. From the SEIQHRF model for Nizamuddin we observe in the second phase the number of infected individuals had seen a multitudinous increase in the states where Nizamuddin attendees returned, increasing the risk of the disease spread. However, the simulations reveal that implementing administrative interventions, flatten the curve. In Dharavi, through tracing, tracking, testing and treating, massive breakout of COVID-19 was brought under control. Conclusions The cluster analysis performed on the districts reveal homogeneous groups of districts that can be ranked based on the burden placed on the healthcare system in terms of number of confirmed cases, population density and number of hospitals dedicated to COVID-19 treatment. The study rounds up with two important case studies on Nizamuddin basti and Dharavi to illustrate the growth curve of COVID-19 in two very densely populated regions in India. In the case of Nizamuddin, the study showed that there was a manifold increase in the risk of infection. In contrast it is seen that there was a rapid decline in the number of cases in Dharavi within a span of about one month.

scholarly journals Impact of reduction of susceptibility to SARS-CoV-2 on epidemic dynamics in four early-seeded metropolitan regions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Thomas J. Barrett ◽  
Karen C. Patterson ◽  
Timothy M. James ◽  
Peter Krüger
Keyword(s):  
Public Health ◽  
Growth Phase ◽  
Chronic Phase ◽  
Health Interventions ◽  
Resource Utilisation ◽  
Policy Planning ◽  
Infection Rates ◽  
Public Health Interventions ◽  
Metropolitan Regions ◽  
Epidemic Dynamics

AbstractAs we enter a chronic phase of the SARS-CoV-2 pandemic, with uncontrolled infection rates in many places, relative regional susceptibilities are a critical unknown for policy planning. Tests for SARS-CoV-2 infection or antibodies are indicative but unreliable measures of exposure. Here instead, for four highly-affected countries, we determine population susceptibilities by directly comparing country-wide observed epidemic dynamics data with that of their main metropolitan regions. We find significant susceptibility reductions in the metropolitan regions as a result of earlier seeding, with a relatively longer phase of exponential growth before the introduction of public health interventions. During the post-growth phase, the lower susceptibility of these regions contributed to the decline in cases, independent of intervention effects. Forward projections indicate that non-metropolitan regions will be more affected during recurrent epidemic waves compared with the initially heavier-hit metropolitan regions. Our findings have consequences for disease forecasts and resource utilisation.

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