Public Health Interventions for Asthma, An Umbrella Review, 1990–2010

SciVee ◽  
2012 ◽  
Author(s):  
Magdala Labre ◽  
PhD PhD ◽  
MPH MPH ◽  
Elizabeth Herman ◽  
MD MD ◽  
...  
Keyword(s):  
Public Health ◽  
Health Interventions ◽  
Umbrella Review ◽  
Public Health Interventions

scholarly journals Which public health interventions are effective in reducing morbidity, mortality and health inequalities from infectious diseases amongst children in low-income and middle-income countries (LMICs): protocol for an umbrella review

BMJ Open ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. e032981
Author(s):  
Elodie Besnier ◽  
Katie Thomson ◽  
Donata Stonkute ◽  
Talal Mohammad ◽  
Nasima Akhter ◽  
...  
Keyword(s):  
Public Health ◽  
Global Health ◽  
Infectious Diseases ◽  
Health Inequalities ◽  
Low Income ◽  
Health Interventions ◽  
Umbrella Review ◽  
Public Health Interventions ◽  
Middle Income ◽  
Middle Income Countries

IntroductionDespite significant progress in the last few decades, infectious diseases remain a significant threat to children’s health in low-income and middle-income countries. Effective means of prevention and control for these diseases exist, making any differences in the burden of these diseases between population groups or countries inequitable. Yet, gaps remain in our knowledge of the effect these public health interventions have on health inequalities in children, especially in low-income and middle-income countries. This umbrella review aims to address some of these gaps by exploring which public health interventions are effective in reducing morbidity, mortality and health inequalities from infectious diseases among children in low-income and middle-income countries.Methods and analysisAn umbrella review will be conducted to identify systematic reviews or evidence synthesis of public health interventions that reduce morbidity, mortality and/or health inequalities due to infectious diseases among children (aged under 5 years) in low-income and middle-income countries. The interventions of interest are public health interventions targeting infectious diseases or associated risk factors in children. We will search for reviews reporting health and health inequalities outcomes in and between populations. The literature search will be undertaken using the Cochrane Library, Medline, EMBASE, the CAB Global Health database, Health Evidence, the Campbell Collaboration Library of Systematic Reviews, International Initiative for Impact Evaluation Systematic review repository, Scopus, the Social Sciences Citation Index and PROSPERO. Additionally, a manual search will be performed in Google Scholar and three international organisations websites (UNICEF Office of Research—Innocenti, UNICEF, WHO) to capture grey literature. Data from the records meeting our inclusion/exclusion criteria will be collated using a narrative synthesis approach.Ethics and disseminationThis review will exclusively work with anonymous group-level information available from published reviews. No ethical approval was required.The results of the review will be submitted for publication in academic journals and presented at international public health conferences. Additionally, key findings will be summarised for dissemination to a wider policy and general public audience as part of the Centre for Global Health Inequalities Research’s policy work.PROSPERO registration numberCRD42019141673

scholarly journals Which public health interventions are effective in reducing morbidity, mortality and health inequalities from infectious diseases amongst children in low- and middle-income countries (LMICs): An umbrella review

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0251905
Author(s):  
Elodie Besnier ◽  
Katie Thomson ◽  
Donata Stonkute ◽  
Talal Mohammad ◽  
Nasima Akhter ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Health Inequalities ◽  
Systematic Reviews ◽  
Health Interventions ◽  
Umbrella Review ◽  
Public Health Interventions ◽  
Middle Income ◽  
Middle Income Countries ◽  
Disadvantaged Groups

Despite significant progress in the last few decades, infectious diseases remain a major threat to child health in low- and middle-income countries (LMICs)—particularly amongst more disadvantaged groups. It is imperative to understand the best available evidence concerning which public health interventions reduce morbidity, mortality and health inequalities in children aged under five years. To address this gap, we carried out an umbrella review (a systematic reviews of reviews) to identify evidence on the effects of public health interventions (promotion, protection, prevention) on morbidity, mortality and/or health inequalities due to infectious diseases amongst children in LMICs. Ten databases were searched for records published between 2014–2021 alongside a manual search of gray literature. Articles were quality-assessed using the Assessment of Multiple Systematic Reviews tool (AMSTAR 2). A narrative synthesis was conducted. We identified 60 systematic reviews synthesizing 453 individual primary studies. A majority of the reviews reported on preventive interventions (n = 48), with a minority on promotion (n = 17) and almost no reviews covering health protection interventions (n = 2). Effective interventions for improving child health across the whole population, as well as the most disadvantaged included communication, education and social mobilization for specific preventive services or tools, such as immunization or bed nets. For all other interventions, the effects were either unclear, unknown or detrimental, either at the overall population level or regarding health inequalities. We found few reviews reporting health inequalities information and the quality of the evidence base was generally low. Our umbrella review identified some prevention interventions that might be useful in reducing under five mortality from infectious diseases in LMICs, particularly amongst the most disadvantaged groups.

Novel conceptual framework and toolset for country-wide assessments of opportunities and challenges for public health interventions

2011 ◽  
Vol 4 (0) ◽  
Author(s):  
Scott McNabb ◽  
Joseph Wamala ◽  
Anila Naz ◽  
Anna Hartrampf ◽  
Dan Samoly ◽  
...  
Keyword(s):  
Public Health ◽  
Conceptual Framework ◽  
Health Interventions ◽  
Public Health Interventions

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.

scholarly journals Evolution of disease transmission during the COVID-19 pandemic: patterns and determinants

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Zhu ◽  
Blanca Gallego
Keyword(s):  
Public Health ◽  
Disease Transmission ◽  
Clustering Algorithm ◽  
Health Interventions ◽  
Transmission Model ◽  
Model Parameters ◽  
Public Health Interventions ◽  
Forecasting Accuracy ◽  
Time Lagged ◽  
The Impact

AbstractEpidemic models are being used by governments to inform public health strategies to reduce the spread of SARS-CoV-2. They simulate potential scenarios by manipulating model parameters that control processes of disease transmission and recovery. However, the validity of these parameters is challenged by the uncertainty of the impact of public health interventions on disease transmission, and the forecasting accuracy of these models is rarely investigated during an outbreak. We fitted a stochastic transmission model on reported cases, recoveries and deaths associated with SARS-CoV-2 infection across 101 countries. The dynamics of disease transmission was represented in terms of the daily effective reproduction number ($$R_t$$ R t ). The relationship between public health interventions and $$R_t$$ R t was explored, firstly using a hierarchical clustering algorithm on initial $$R_t$$ R t patterns, and secondly computing the time-lagged cross correlation among the daily number of policies implemented, $$R_t$$ R t , and daily incidence counts in subsequent months. The impact of updating $$R_t$$ R t every time a prediction is made on the forecasting accuracy of the model was investigated. We identified 5 groups of countries with distinct transmission patterns during the first 6 months of the pandemic. Early adoption of social distancing measures and a shorter gap between interventions were associated with a reduction on the duration of outbreaks. The lagged correlation analysis revealed that increased policy volume was associated with lower future $$R_t$$ R t (75 days lag), while a lower $$R_t$$ R t was associated with lower future policy volume (102 days lag). Lastly, the outbreak prediction accuracy of the model using dynamically updated $$R_t$$ R t produced an average AUROC of 0.72 (0.708, 0.723) compared to 0.56 (0.555, 0.568) when $$R_t$$ R t was kept constant. Monitoring the evolution of $$R_t$$ R t during an epidemic is an important complementary piece of information to reported daily counts, recoveries and deaths, since it provides an early signal of the efficacy of containment measures. Using updated $$R_t$$ R t values produces significantly better predictions of future outbreaks. Our results found variation in the effect of early public health interventions on the evolution of $$R_t$$ R t over time and across countries, which could not be explained solely by the timing and number of the adopted interventions.

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