Evaluation of community-based public health interventions: the centered evaluation guidebook

2003 ◽  
Vol 13 (8) ◽  
pp. 589
Author(s):  
D.J Goodwin
2021 ◽  
Vol 9 ◽  
Author(s):  
Amelie Cyr ◽  
Prosanta Mondal ◽  
Gregory Hansen

Objectives: According to the World Health Organization (WHO), an early and consistent international and national response is needed to control a pandemic's spread. In this analysis, we evaluate the coordination of Canada's early response to the coronavirus (COVID-19) pandemic in terms of public health interventions and policies implemented in each province and territory.Methods: Retrospective data was obtained from publicly accessible websites maintained by federal, provincial and territorial governmental agencies. Consistent with WHO's spreading of the disease pandemic action, individual and community-based public health interventions and policies were the focus. Time of intervention or policy, and COVID-19 cases per million at time of intervention was recorded for each province and territory.Results: Most public health interventions and policies demonstrated wide time ranges of implementation across individual provinces and territories. At time of implementation, there were also wide variations in the number of positive COVID-19 cases in these jurisdictions. Cases per million per implemented day were also not similar across interventions or policy, suggesting that other factors may have been preferentially considered.Conclusions: Whether an earlier and more structured national approach would have lessened the pandemic's burden is uncertain, calls for greater federal coordination and leadership should to examined.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pooja Sengupta ◽  
Bhaswati Ganguli ◽  
Sugata SenRoy ◽  
Aditya Chatterjee

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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Thomas J. Barrett ◽  
Karen C. Patterson ◽  
Timothy M. James ◽  
Peter Krüger

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.


Sign in / Sign up

Export Citation Format

Share Document