Locality based Approach for containment of COVID-19 Infections in Pakistan’s High risk Districts-ICT

Abstract Background In May 2020, considering gradual restoration of all economical activities the Government of Pakistan updated containment strategy from locking down the whole country to locking down high-risk areas to mitigate COVID-19 spread. All districts having ≥300 cases/100,000 population. COVID-19 case incidence and test positivity rates by real-time RT-PCR before and after zonal lockdown were compared to assess whether the locality-based lockdowns can be used as an alternative to country lockdown to contain COVID-19 spread. Methods Smart lockdowns were implemented in ten localities in the Islamabad Capital Territory (ICT), having a population of 60,000 from 12 May 2020 to June 3, 2020. Movements were restricted. Entry and exit points were guarded by police. Any person with symptoms of fever, cough, or sore throat tested by real-time RT-PCR methods and reported within 24 hours of collection. To compare the rate of active cases and positivity rate by weeks, we performed a z-test for two proportions and set p < 0.05 as the level of significance. Results The red zone had 60,000 persons in 2.00 square kilometers. The rate of active COVID-19 cases significantly decreased (p < 0.0001) during intervention from 300/100,000 population pre-containment time to 22/100,000 population after the first three weeks of lockdown. The COVID-19 positivity rate also decreased significantly (p < 0.0001) from 24% (24/78) pre-containment to 5.3% during containment. A total of 3800 people were tested in the following three weeks of intervention and 26 cases were detected. Conclusions The smart lockdowns approach reduced COVID-19 transmission in the ICT district. This type of intervention was recommended to reduce the COVID-19 infection spread Key messages • Reduced COVID-19 transmission in the ICT district. • Keeping balance between life and economy.


Background:
The COVID-19 pandemic has changed the way infectious diseases are perceived. Global healthcare systems have faced challenges since the start of the COVID-19 epidemic, particularly in developing countries. Some individuals with an acute COVID-19 diagnosis have developed symptoms persisting beyond 90 days. Long-Covid is the new term for this syndrome (LC). LC, on the other hand, is poorly known and appears to cause a wide range of symptoms, particularly among Brazilian patients. As a result, utilizing retrospective data from patients in Petrolina, Brazil's largest city in the northeast, we conducted an exploratory epidemiology study.

Methods:
A retrospective, cohort study design was used with a real-world dataset. The primary aim was to evaluate the prevalence of LC within Petrolina. The sample size was 1,164 LC patients. A comparative and subgroup analysis was conducted to evaluate demographics, comorbidities, clinical symptoms, and mortality. A k means model was used to assess disease severity using a clustering analysis based on the presence of comorbidities.

Results:
The prevalence of physical symptoms identified was 69Á5%. The strongest physical symptom was fever with resultant of 64Á09% followed by pain, 43Á64%. The prevalence of autonomic and neurological symptomatology was 8Á59% and 8Á16% respectively. A higher prevalence of autonomic symptoms were reported among older men of Black and Caucasian in comparison to Pardo. Disease severity within the sample could be associated with the presence of comorbidities which were identified based on medication history. Pregnant women have high rate of comorbidities. 529 patients have at least one comorbidity and 28Á73% of them are pregnant.

Conclusions:
It is useful to evaluate symptoms although a definitive diagnosis of LC is essential. This study provides insightful information around LC within a Brazilian population to develop better infection control protocols, as well as future management of similar pandemics.

Key messages:
This study could potentially improve the prognosis and mortality among LC patients with comorbidities. Our findings could be combined with other regional datasets to predict pattern inferences of LC spread, prognosis and morbidity, including for multimorbidity and pregnant patients.

Background:
In May 2020, considering gradual restoration of all economical activities the Government of Pakistan updated containment strategy from locking down the whole country to locking down high-risk areas to mitigate COVID-19 spread. All districts having !300 cases/100,000 population. COVID-19 case incidence and test positivity rates by real-time RT-PCR before and after zonal lockdown were compared to assess whether the locality-based lockdowns can be used as an alternative to country lockdown to contain COVID-19 spread.

Methods:
Smart lockdowns were implemented in ten localities in the Islamabad Capital Territory (ICT), having a population of 60,000 from 12 May 2020 to June 3, 2020. Movements were restricted. Entry and exit points were guarded by police. Any person with symptoms of fever, cough, or sore throat tested by real-time RT-PCR methods and reported within 24 hours of collection. To compare the rate of active cases and positivity rate by weeks, we performed a z-test for two proportions and set p < 0.05 as the level of significance.

Results:
The red zone had 60,000 persons in 2.00 square kilometers. The rate of active COVID-19 cases significantly decreased (p < 0.0001) during intervention from 300/100,000 population pre-containment time to 22/100,000 population after the first three weeks of lockdown. The COVID-19 positivity rate also decreased significantly (p < 0.0001) from 24% (24/78) precontainment to 5.3% during containment. A total of 3800 people were tested in the following three weeks of intervention and 26 cases were detected.

Conclusions:
The smart lockdowns approach reduced COVID-19 transmission in the ICT district. This type of intervention was recommended to reduce the COVID-19 infection spread

Methods:
We used data from the prospective multigenerational Dutch Lifelines Cohort Study. Our sample consisted of 6,683 children with an average follow-up of 36.2 months (SD 9.3) and a mean baseline age of 12.8 years (SD 2.6). We used natural effects models to assess the natural direct, natural indirect, and total effects of parental SES on MetS.