The Impact of Disease Control Measures on the Spread of COVID-19 in the Province of Sindh, Pakistan
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ABSTRACT:
SUBMITTER: Usmani B
PROVIDER: S-EPMC8601461 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundMultiple Coronavirus Disease 2019 (COVID-19) vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh Province, Pakistan (population: 48 million).Methods and findingsWe fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalisation outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability-adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario. We project that 1 year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70% efficacy and 2.5-year duration of protection is likely to avert around 0.9 (95% credible interval (CrI): 0.9, 1.0) million cases, 10.1 (95% CrI: 10.1, 10.3) thousand deaths, and 70.1 (95% CrI: 69.9, 70.6) thousand DALYs, with an ICER of $27.9 per DALY averted from the health system perspective. Under a broad range of alternative scenarios, we find that initially prioritising the older (65+) population generally prevents more deaths. However, unprioritised distribution has almost the same cost-effectiveness when considering all outcomes, and both prioritised and unprioritised programmes can be cost-effective for low per-dose costs. High vaccine prices ($10/dose), however, may not be cost-effective, depending on the specifics of vaccine performance, distribution programme, and future pandemic trends. The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age-specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses. This study is limited by model approximations, available data, and future uncertainty. Because the model is a single-population compartmental model, detailed impacts of nonpharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritising groups like healthcare or other essential workers. The model is only fitted to the reported case and death data, which are incomplete and not disaggregated by, e.g., age. Finally, because the future impact and implementation cost of NPIs are uncertain, how these would interact with vaccination remains an open question.ConclusionsCOVID-19 vaccination can have a considerable health impact and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact. However, the advantage of prioritising older, high-risk populations is smaller in generally younger populations. This reduction is especially true in populations with more past transmission, and if the vaccine is likely to further impede transmission rather than just disease. Those conditions are typical of many low- and middle-income countries.
| S-EPMC8523052 | biostudies-literature
Project description:The novel coronavirus (COVID-19) pandemic is causing devastating demographic, social, and economic damage globally. Understanding current patterns of the pandemic spread and forecasting its long-term trajectory is essential in guiding policies aimed at curtailing the pandemic. This is particularly important in regions with weak economies and fragile health care systems such as West Africa. We formulate and use a deterministic compartmental model to (i) assess the current patterns of COVID-19 spread in West Africa, (ii) evaluate the impact of currently implemented control measures, and (iii) predict the future course of the pandemic with and without currently implemented and additional control measures in West Africa. An analytical expression for the threshold level of control measures (involving a reduction in the effective contact rate) required to curtail the pandemic is computed. Considering currently applied health control measures, numerical simulations of the model using baseline parameter values estimated from West African COVID-19 data project a 67% reduction in the daily number of cases when the epidemic attains its peak. More reduction in the number of cases will be achieved if additional public health control measures that result in a reduction in the effective contact rate are implemented. We found out that disease elimination is difficult when more asymptomatic individuals contribute in transmission or are not identified and isolated in a timely manner. However, maintaining a baseline level of asymptomatic isolation and a low transmission rate will lead to a significant reduction in the number of daily cases when the pandemic peaks. For example, at the baseline level of asymptomatic isolation, at least a 46% reduction in the transmission rate is required for disease elimination. Additionally, disease elimination is possible if asymptomatic individuals are identified and isolated within 5 days (after the incubation period). Combining two or more measures is better for disease control, e.g., if asymptomatic cases are contact traced or identified and isolated in less than 8 days, only about 29% reduction in the disease transmission rate is required for disease elimination. Furthermore, we showed that the currently implemented measures triggered a 33% reduction in the time-dependent effective reproduction number between February 28 and June 26, 2020. We conclude that curtailing the COVID-19 pandemic burden significantly in West Africa requires more control measures than those that have already been implemented, as well as more mass testing and contact tracing in order to identify and isolate asymptomatic individuals early.
| S-EPMC7388784 | biostudies-literature
Project description:ABSTRACTThe COVID-19 pandemic and measures against it provided a unique opportunity to understand the transmission of other infectious diseases and to evaluate the efficacy of COVID-19 prevention measures on them. Here we show a dengue epidemic in Yunnan, China, during the pandemic of COVID-19 was dramatically reduced compared to non-pandemic years and, importantly, spread was confined to only one city, Ruili. Three key features characterized this dengue outbreak: (i) the urban-to-suburban spread was efficiently blocked; (ii) the scale of epidemic in urban region was less affected; (iii) co-circulation of multiple strains was attenuated. These results suggested that countermeasures taken during COVID-19 pandemic are efficient to prevent dengue transmission between cities and from urban to suburban, as well to reduce the co-circulation of multiple serotypes or genotypes. Nevertheless, as revealed by the spatial analysis, once the dengue outbreak was established, its distribution was very stable and resistant to measures against COVID-19, implying the possibility to develop a precise prediction method.
| S-EPMC8745368 | biostudies-literature
Project description:BackgroundCOVID-19 pandemic has affected routine immunization globally. Impact will likely be higher in low and middle-income countries with limited healthcare resources and fragile health systems. We quantified the impact, spatial heterogeneity, and determinants for childhood immunizations of 48 million population affected in the Sindh province of Pakistan.MethodsWe extracted individual immunization records from real-time provincial Electronic Immunization Registry from September 23, 2019, to July 11, 2020. Comparing baseline (6 months preceding the lockdown) and the COVID-19 lockdown period, we analyzed the impact on daily immunization coverage rate for each antigen by geographical area. We used multivariable logistic regression to explore the predictors associated with immunizations during the lockdown.ResultsThere was a 52.5% decline in the daily average total number of vaccinations administered during lockdown compared to baseline. The highest decline was seen for Bacille Cal-mette Guérin (BCG) (40.6% (958/2360) immunization at fixed sites. Around 8438 children/day were missing immunization during the lockdown. Enrollments declined furthest in rural districts, urban sub-districts with large slums, and polio-endemic super high-risk sub-districts. Pentavalent-3 (penta-3) immunization rates were higher in infants born in hospitals (RR: 1.09; 95% CI: 1.04-1.15) and those with mothers having higher education (RR: 1.19-1.50; 95% CI: 1.13-1.65). Likelihood of penta-3 immunization was reduced by 5% for each week of delayed enrollment into the immunization program.ConclusionOne out of every two children in Sindh province has missed their routine vaccinations during the provincial COVID-19 lockdown. The pool of un-immunized children is expanding during lockdown, leaving them susceptible to vaccine-preventable diseases. There is a need for tailored interventions to promote immunization visits and safe service delivery. Higher maternal education, facility-based births, and early enrollment into the immunization program continue to show a positive association with immunization uptake, even during a challenging lockdown.
| S-EPMC7428732 | biostudies-literature
Project description:The rapid expansion of coronavirus disease 2019 (COVID-19) has been observed in many parts of the world. Many newly reported cases of COVID-19 during early outbreak phases have been associated with travel history from an epidemic region (identified as imported cases). For those cases without travel history, the risk of wider spreads through community contact is even higher. However, most population models assume a homogeneous infected population without considering that the imported and secondary cases contracted by the imported cases can pose different risks to community spread. We have developed an "easy-to-use" mathematical framework extending from a meta-population model embedding city-to-city connections to stratify the dynamics of transmission waves caused by imported, secondary, and others from an outbreak source region when control measures are considered. Using the cumulative number of the secondary cases, we are able to determine the probability of community spread. Using the top 10 visiting cities from Wuhan in China as an example, we first demonstrated that the arrival time and the dynamics of the outbreaks at these cities can be successfully predicted under the reproduction number R0 = 2.92 and incubation period ? = 5.2 days. Next, we showed that although control measures can gain extra 32.5 and 44.0 days in arrival time through an intensive border control measure and a shorter time to quarantine under a low R0 (1.4), if the R0 is higher (2.92), only 10 extra days can be gained for each of the same measures. This suggests the importance of lowering the incidence at source regions together with infectious disease control measures in susceptible regions. The study allows us to assess the effects of border control and quarantine measures on the emergence and global spread of COVID-19 in a fully connected world using the dynamics of the secondary cases.
| S-EPMC7274973 | biostudies-literature
Project description:BackgroundDuring the early stage of the COVID-19 pandemic, many countries implemented non-pharmaceutical interventions (NPIs) to control the transmission of SARS-CoV-2, the causative pathogen of COVID-19. Among those NPIs, stay-at-home and quarantine measures were widely adopted and enforced. Understanding the effectiveness of stay-at-home and quarantine measures can inform decision-making and control planning during the ongoing COVID-19 pandemic and for future disease outbreaks.MethodsIn this study, we use mathematical models to evaluate the impact of stay-at-home and quarantine measures on COVID-19 spread in four cities that experienced large-scale outbreaks in the spring of 2020: Wuhan, New York, Milan, and London. We develop a susceptible-exposed-infected-removed (SEIR)-type model with components of self-isolation and quarantine and couple this disease transmission model with a data assimilation method. By calibrating the model to case data, we estimate key epidemiological parameters before lockdown in each city. We further examine the impact of stay-at-home and quarantine rates on COVID-19 spread after lockdown using counterfactual model simulations.ResultsResults indicate that self-isolation of susceptible population is necessary to contain the outbreak. At a given rate, self-isolation of susceptible population induced by stay-at-home orders is more effective than quarantine of SARS-CoV-2 contacts in reducing effective reproductive numbers [Formula: see text]. Variation in self-isolation and quarantine rates can also considerably affect the duration of outbreaks, attack rates and peak timing. We generate counterfactual simulations to estimate effectiveness of stay-at-home and quarantine measures. Without these two measures, the cumulative confirmed cases could be much higher than reported numbers within 40 days after lockdown in Wuhan, New York, Milan, and London.ConclusionsOur findings underscore the essential role of stay-at-home orders and quarantine of SARS-CoV-2 contacts during the early phase of the pandemic.
| S-EPMC9326419 | biostudies-literature
Project description:Low Birth Weight (LBW) is considered as a major public health issue and leading cause of neonatal death. Almost one in four newborns are reported as underweight in Pakistan. Children born with low birth weight are highly vulnerable to develop diseases and death and/or remain undernourished (i.e., stunted and wasted). This study determines the LBW newborns are more prone to develop stunting and wasting in province of Sindh, Pakistan. Moreover, regression-based estimation of the impact of LBW on the child health outcomes of under five years of age, may be prone to selection bias because of the nature of non-experimental data set, thus, propensity score matching methods are used in this study. Data for this study was used from Multiple Indicators Cluster Survey (MICS-2014). MICS is a two-stage, stratified cluster sampling household level data covering urban and rural areas and consists of 19,500 households from five administrative divisions and 28 districts of Sindh province of Pakistan. The total sample size of children less than five years of age after cleaning the data are 7781, of which 2095 are LBW having birth weight categorized as "smaller than average and very small" and 5686 are normal birth weight (NBW) having birth weight very large, larger than average, and average. This study employed propensity score matching (PSM) regression methods to understand whether the children born as low birth weight are more prone to stunting and wasting and/or both. In province of Sindh, moderate wasting children under five years were 21%, severe wasting 6% and both wasting and stunting 10%. The propensity score results are shown significant in all groups. Specifically, all four types of PSM methods confirm a significant difference in the potential outcome variables-meaning that a child born with LBW has a significant adverse effect on the potential child health outcome variables (stunting, wasting and both). Thus, the propensity score matching findings confirm a significant and adverse effect of LBW on potential health outcomes of under five children. Similarly, low birth weight children are significantly more likely to be moderately wasted (OR = 1.5, CI = 1.3-1.6) and severely wasted (OR = 1.6, CI = 1.3-2.0) and both (stunted and wasted, OR = 2.0, CI = 1.7-2.3) as compared to children with normal birth weight. Male children, if born with low birth weight, are significantly more likely to be moderately wasted (OR = 1.3, CI = 1.1-1.5) and both (wasted and stunted, OR = 1.3, CI = 1.1-1.5) than girls. This large data analysis finding proved that the LBW newborns are on higher risk to develop wasting and stunting in Pakistan.
| S-EPMC8497567 | biostudies-literature
Project description:BACKGROUND:Antenatal care (ANC) is critical to decrease maternal and neonatal mortality. However, little is known about the utilization of ANC services in Pakistan. This study assessed the utilization of ANC in Sindh province, Pakistan, and identified the factors that affect its use. METHODS:We analysed a subset of data from Maternal and Child Health (MCH) Program Indicator Surveys conducted in Sindh province, Pakistan in 2013 and 2014. Respondents included 10,200 women who had given birth in the past two years. The outcome measure was making at least four ANC visits. Logistic regression models were used to identify demographic, socioeconomic, characteristics of ANC, and informational factors associated with ANC use. RESULTS:Most women (83.5%) received one or more ANC, mostly by doctors (95%), but only 57.3% of them made the recommended four or more visits, and just 53.7% received their initial ANC care during the first trimester. Making four or more ANC visits was associated with: fewer household occupants (odds ratio [OR] = 0.98; 95% confidence interval [CI] = [0.97, 0.99]), large city residence (OR = 1.92; 95% CI = [1.57, 2.35]), higher women's education (OR = 1.70; 95% CI = [1.33, 2.15]), greater household wealth (OR = 5.66; 95% CI = [4.22, 7.60]), and receiving MCH information from lady health worker (OR = 1.17; 95% CI = [1.00, 1.37]), mother-in-law (OR = 1.17; 95% CI = [1.01, 1.36]), other relatives/friends (OR = 1.19; 95% CI = [1.03, 1.38]), or nurse/midwife (OR = 1.31; 95% CI = [1.06, 1.61]). CONCLUSIONS:This study demonstrates that both socioeconomic factors and health information sources are associated with women's use of ANC. Therefore, programs should target socially disadvantaged and vulnerable groups, particularly rural, less educated, and poor women, to improve utilization of ANC. In addition, strategies to increase exposure to MCH information sources should be a priority in Sindh, Pakistan.
| S-EPMC6447146 | biostudies-literature
Project description:BackgroundAt present, India is in the decreasing phase of the second wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). But India as a country is in the second position in a high number of confirmed cases (33,678,786) in the world (after the United States of America) and third position in the number of COVID-19 deaths (after the United States and Brazil) at 465,082 deaths. Almost above numbers are dominantly seen in the second wave only. Thus, future long-term projections are required to mitigate the impact.MethodsThe conventional SIR model was modified so that a new compartment Q(quarantine) is added to the conventional SIR model to analyze the COVID-19 impact. The parameter optimal control technique was used to fit the curve by estimating the infection, susceptible, etc.ResultsThe model predicts the cumulative number of cases of 2.6928E7 with a confidence interval of 95%, CI[2.6921E7,2.6935E7], and an accuracy of 99.3% on May 25, 2020(480th day from 30 to 01-2020). The estimated R0 is 1.1475. The model's mean absolute error(E MAE ) is 1.79E4, and the root-mean-square error is (E RMSE ) is 3.19E4. The future projection are,3.48E7(Lockdown), 3.80E7(periodic-lockdown), 4.52E7(without lockdown). The whole model accuracy is 99%, and projection accuracy is about 94% up to 01-Nov-2021, The goodness of fit value 0.8954.ConclusionThe model is over-estimating corona cases initially and then showed a decreased trend. As the number of days increases, the model accuracy decreases; thus, more control points of the cost function are required to fit the model best.
| S-EPMC8668862 | biostudies-literature
Project description:BackgroundThe COVID-19 virus has been an emerging disease causing global outbreaks for over a year. In Thailand, transmission may be controlled by strict measures that could positively and negatively impact physical health and suicidal behavior.MethodsThe incidence of COVID-19 was retrieved from the Department of Disease Control (DDC). The impact of viral diseases was retrieved from the open-source of the DDC and King Chulalongkorn Memorial Hospital. The road accidents data were from the Thai Ministry of Transport. The suicidal behavior data were obtained from the Department of Mental Health. We compared data from the year 2019 with the pandemic COVID-19 outbreak period in 2020, before lockdown, during lockdown, easing, and new wave period using unpaired t-test and least-squares linear regression. We compared the impact of the outbreak on various data records in 2020 with corresponding non-outbreak from 2019.ResultsThere was a significant decline in cases of influenza (p < 0.001) and norovirus (p = 0.01). However, there was no significant difference in RSV cases (p = 0.17). There was a dramatic increase in attempt to suicides and suicides (p < 0.001). There was no impact on roadside accidents and outpatient department visits.DiscussionThe extensive intervention measures during lockdown during the first wave positively impacted total cases for each period for acute respiratory and gastrointestinal tract diseases, car accidents, and injuries and negatively impacted indicators of suicidal behavior. The data support government policies that would be effective against the next outbreak by promoting the "new normal" lifestyle.
| S-EPMC8857899 | biostudies-literature