The Impact of Non-Pharmaceutical Interventions on Unemployment During a Pandemic

2020 ◽  
Author(s):  
Edward Kong ◽  
Daniel Prinz
Keyword(s):  
The Impact ◽  
Pharmaceutical Interventions

The Impact of COVID-19 Quarantine on Children‘s Behaviors and Language

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 796-806
Author(s):  
Sana M Kamal ◽  
Ali Al-Samydai ◽  
Rudaina Othman Yousif ◽  
Talal Aburjai
Keyword(s):  
Social Relations ◽  
Child Psychology ◽  
Simple Random Sample ◽  
Community Pharmacies ◽  
The World ◽  
Female Children ◽  
And Behavior ◽  
The Impact ◽  
Pharmaceutical Interventions

COVID-19 pandemic has spread across the world, which considered a relative of the severe acute respiratory syndrome (SARS), with possibility of transmission from animals to human and effect each of health and economic. Several preventative strategies and non-pharmaceutical interventions have been used to slow down the spread of COVID-19. The questionnaire contained 36 questions regarding the impact of COVID-19 quarantine on children`s behaviors and language have been distributed online (Google form). Data collected after asking parents about their children behavior during quarantine, among the survey completers (n=469), 42.3% were female children, and 57.7 were male children. Results showed that quarantine has an impact on children`s behaviors and language, where stress and isolationism has a higher effect, while social relations had no impact. The majority of the respondents (75.0%) had confidence that community pharmacies can play an important role in helping families in protection their children`s behaviors and language as they made the highest contact with pharmacists during quarantine. One of the main recommendations that could be applied to help parents protection and improvement their children`s behaviors and language in quarantine condition base on simple random sample opinion is increasing the role of community pharmacies inpatient counseling and especially towards children after giving courses to pharmacists in child psychology and behavior. This could be helpful to family to protect their children, from any changing in them behaviors and language in such conditions in the future if the world reface such the same problem.

scholarly journals The effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in different socioeconomic populations in Kuwait: a modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fatima Khadadah ◽  
Abdullah A. Al-Shammari ◽  
Ahmad Alhashemi ◽  
Dari Alhuwail ◽  
Bader Al-Saif ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Reproduction Number ◽  
Transmission Model ◽  
Socioeconomic Groups ◽  
Before And After ◽  
Cross Transmission ◽  
Community Transmission ◽  
The Impact ◽  
Pharmaceutical Interventions ◽  
The Basic Reproduction Number

Abstract Background Aggressive non-pharmaceutical interventions (NPIs) may reduce transmission of SARS-CoV-2. The extent to which these interventions are successful in stopping the spread have not been characterized in countries with distinct socioeconomic groups. We compared the effects of a partial lockdown on disease transmission among Kuwaitis (P1) and non-Kuwaitis (P2) living in Kuwait. Methods We fit a modified metapopulation SEIR transmission model to reported cases stratified by two groups to estimate the impact of a partial lockdown on the effective reproduction number ($$ {\mathcal{R}}_e $$ R e ). We estimated the basic reproduction number ($$ {\mathcal{R}}_0 $$ R 0 ) for the transmission in each group and simulated the potential trajectories of an outbreak from the first recorded case of community transmission until 12 days after the partial lockdown. We estimated $$ {\mathcal{R}}_e $$ R e values of both groups before and after the partial curfew, simulated the effect of these values on the epidemic curves and explored a range of cross-transmission scenarios. Results We estimate $$ {\mathcal{R}}_e $$ R e at 1·08 (95% CI: 1·00–1·26) for P1 and 2·36 (2·03–2·71) for P2. On March 22nd, $$ {\mathcal{R}}_e $$ R e for P1 and P2 are estimated at 1·19 (1·04–1·34) and 1·75 (1·26–2·11) respectively. After the partial curfew had taken effect, $$ {\mathcal{R}}_e $$ R e for P1 dropped modestly to 1·05 (0·82–1·26) but almost doubled for P2 to 2·89 (2·30–3·70). Our simulated epidemic trajectories show that the partial curfew measure greatly reduced and delayed the height of the peak in P1, yet significantly elevated and hastened the peak in P2. Modest cross-transmission between P1 and P2 greatly elevated the height of the peak in P1 and brought it forward in time closer to the peak of P2. Conclusion Our results indicate and quantify how the same lockdown intervention can accentuate disease transmission in some subpopulations while potentially controlling it in others. Any such control may further become compromised in the presence of cross-transmission between subpopulations. Future interventions and policies need to be sensitive to socioeconomic and health disparities.

scholarly journals SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study

2021 ◽  
Vol 8 (3) ◽  
Author(s):  
Qimin Huang ◽  
Anirban Mondal ◽  
Xiaobing Jiang ◽  
Mary Ann Horn ◽  
Fei Fan ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
Hospital Setting ◽  
Credible Interval ◽  
Hospital Unit ◽  
Early Implementation ◽  
Using Data ◽  
And Control ◽  
The Impact ◽  
Pharmaceutical Interventions ◽  
Outbreak Size

Development of strategies for mitigating the severity of COVID-19 is now a top public health priority. We sought to assess strategies for mitigating the COVID-19 outbreak in a hospital setting via the use of non-pharmaceutical interventions. We developed an individual-based model for COVID-19 transmission in a hospital setting. We calibrated the model using data of a COVID-19 outbreak in a hospital unit in Wuhan. The calibrated model was used to simulate different intervention scenarios and estimate the impact of different interventions on outbreak size and workday loss. The use of high-efficacy facial masks was shown to be able to reduce infection cases and workday loss by 80% (90% credible interval (CrI): 73.1–85.7%) and 87% (CrI: 80.0–92.5%), respectively. The use of social distancing alone, through reduced contacts between healthcare workers, had a marginal impact on the outbreak. Our results also indicated that a quarantine policy should be coupled with other interventions to achieve its effect. The effectiveness of all these interventions was shown to increase with their early implementation. Our analysis shows that a COVID-19 outbreak in a hospital's non-COVID-19 unit can be controlled or mitigated by the use of existing non-pharmaceutical measures.

Estimating the Impact of Non-pharmaceutical Interventions Against COVID-19 on Mumps Incidence in Sichuan, China

2021 ◽  
Author(s):  
Wenqiang Zhang ◽  
Rongsheng Luan
Keyword(s):  
Public Health ◽  
Respiratory Virus ◽  
Moving Average ◽  
Sarima Model ◽  
Potential Reduction ◽  
Autoregressive Integrated Moving Average ◽  
Health Measures ◽  
Virus Incidence ◽  
The Impact ◽  
Pharmaceutical Interventions

Abstract Background: A series of social and public health measures have been implemented to contain coronavirus disease 2019 (COVID-19) in China. We examined the impact of non-pharmaceutical interventions against COVID-19 on mumps incidence as an agent to determine the potential reduction in other respiratory virus incidence.Methods: We modelled mumps incidence per month in Sichuan using a seasonal autoregressive integrated moving average (SARIMA) model, based on the reported number of mumps cases per month from 2017-2020. Results: The epidemic peak of mumps in 2020 is lower than in the preceding years. Whenever compared with the projected cases or the average from corresponding periods in the preceding years (2017-2019), the reported cases in 2020 markedly declined (P<0.001). From January to December, the number of mumps cases was estimated to decrease by 36.3% (33.9% - 38.8%), 34.3% (31.1% - 37.8%), 68.9% (66.1% - 71.6%), 76.0% (73.9% - 77.9%), 67.0% (65.0% - 69.0%), 59.6% (57.6% - 61.6%), 61.1% (58.8% - 63.3%), 49.2% (46.4% - 52.1%), 24.4% (22.1% - 26.8%), 30.0% (27.5% - 32.6%), 42.1% (39.6% - 44.7%), 63.5% (61.2% - 65.8%), respectively. The total number of mumps cases in 2020 was estimated to decrease by 53.6% (52.9% - 54.3%).Conclusion: Our study shows that non-pharmaceutical interventions against COVID-19 have had an effective impact on mumps incidence in Sichuan, China.

scholarly journals The impact of national non-pharmaceutical interventions (‘lockdowns’) on the presentation of cancer patients

2021 ◽  
Vol 15 ◽  
Author(s):  
Arnie Purushotham ◽  
Graham Roberts ◽  
Kate Haire ◽  
Joanna Dodkins ◽  
Elizabeth Harvey-Jones ◽  
...  
Keyword(s):  
Cancer Patients ◽  
The Impact ◽  
Pharmaceutical Interventions

scholarly journals Predicting the impact of asymptomatic transmission, non-pharmaceutical intervention and testing on the spread of COVID19

2020 ◽  
Author(s):  
Ira B. Schwartz ◽  
James Kaufman ◽  
Kun Hu ◽  
Simone Bianco
Keyword(s):  
Predictive Models ◽  
Health Interventions ◽  
Strong Impact ◽  
Public Health Interventions ◽  
Removal Time ◽  
The Impact ◽  
Second Wave ◽  
Pharmaceutical Interventions ◽  
Epidemiological Parameters ◽  
Disease Testing

AbstractWe introduce a novel mathematical model to analyze the effect of removing non-pharmaceutical interventions on the spread of COVID19 as a function of disease testing rate. We find that relaxing interventions has a strong impact on the size of the epidemic peak as a function of intervention removal time. We show that it is essential for predictive models to explicitly capture transmission from asymptomatic carriers and important to obtain precise information on asymptomatic transmission by testing. The asymptomatic reservoir, reported to account for as much as 85% of transmission, will contribute to resurgence of the epidemic if public health interventions are removed too soon. Use of more basic models that fail to capture asymptomatic transmission can result in large errors in predicted clinical caseload or in fitted epidemiological parameters and, therefore, may be unreliable in estimating the risk of a second wave based on the timing of terminated interventions.

scholarly journals Simulating the impact of non-pharmaceutical interventions limiting transmission in COVID-19 epidemics using a membrane computing model

microLife ◽  
2021 ◽  
Author(s):  
M Campos ◽  
J M Sempere ◽  
J C Galán ◽  
A Moya ◽  
C Llorens ◽  
...  
Keyword(s):  
Membrane Computing ◽  
Immunological Response ◽  
The Elderly ◽  
Work Activities ◽  
Intervention Measures ◽  
Single Intervention ◽  
The Impact ◽  
Local Parameters ◽  
Pharmaceutical Interventions ◽  
Computing Models

ABSTRACT Epidemics caused by microbial organisms are part of the natural phenomena of increasing biological complexity. The heterogeneity and constant variability of hosts, in terms of age, immunological status, family structure, lifestyle, work activities, social and leisure habits, daily division of time, and other demographic characteristics make it extremely difficult to predict the evolution of epidemics. Such prediction is, however, critical for implementing intervention measures in due time and with appropriate intensity. General conclusions should be precluded, given that local parameters dominate the flow of local epidemics. Membrane computing models allows us to reproduce the objects (viruses, hosts) and their interactions (stochastic but also with defined probabilities) with an unprecedented level of detail. Our LOIMOS model helps reproduce the demographics and social aspects of a hypothetical town of 10,320 inhabitants in an average European country where COVID-19 is imported from the outside. The above-mentioned characteristics of hosts and their lifestyle are minutely considered. For the data in the Hospital and the ICU we took advantage of the observations at the Nursery Intensive Care Unit of the Consortium University General Hospital, Valencia, Spain (included as author). The dynamics of the epidemics are reproduced and include the effects on viral transmission of innate and acquired immunity at various ages. The model predicts the consequences of delaying the adoption of non-pharmaceutical interventions (between 15 and 45 days after the first reported cases) and the effect of those interventions on infection and mortality rates (reducing transmission by 20%, 50%, and 80%) in immunological response groups. The lockdown for the elderly population as a single intervention appears to be effective. This modelling exercise exemplifies the application of membrane computing for designing appropriate multilateral interventions in epidemic situations.

Sign in / Sign up

Export Citation Format

Share Document