Dataset Information

Serial population-based serosurveys for COVID-19 in two neighbourhoods of Karachi, Pakistan.

ABSTRACT:

Objective

To determine population-based estimates of coronavirus disease 2019 (COVID-19) in a densely populated urban community of Karachi, Pakistan.

Methods

Three cross-sectional surveys were conducted in April, June and August 2020 in low- and high-transmission neighbourhoods. Participants were selected at random to provide blood for Elecsys immunoassay for detection of anti-severe acute respiratory syndrome coronavirus-2 antibodies. A Bayesian regression model was used to estimate seroprevalence after adjusting for the demographic characteristics of each district.

Results

In total, 3005 participants from 623 households were enrolled in this study. In Phase 2, adjusted seroprevalence was estimated as 8.7% [95% confidence interval (CI) 5.1-13.1] and 15.1% (95% CI 9.4-21.7) in low- and high-transmission areas, respectively, compared with 0.2% (95% CI 0-0.7) and 0.4% (95% CI 0-1.3) in Phase 1. In Phase 3, it was 12.8% (95% CI 8.3-17.7) and 21.5% (95% CI 15.6-28) in low- and high-transmission areas, respectively. The conditional risk of infection was 0.31 (95% CI 0.16-0.47) and 0.41 (95% CI 0.28-0.52) in low- and high-transmission neighbourhoods, respectively, in Phase 2. Similar trends were observed in Phase 3. Only 5.4% of participants who tested positive for COVID-19 were symptomatic. The infection fatality rate was 1.66%, 0.37% and 0.26% in Phases 1, 2 and 3, respectively.

Conclusion

Continuing rounds of seroprevalence studies will help to improve understanding of secular trends and the extent of infection during the course of the pandemic.

SUBMITTER: Nisar MI

PROVIDER: S-EPMC8752032 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe Government of Pakistan is facing difficulty to contain the surge of COVID-19 due to the country's social, political, economical and cultural context. Experiences from the previous epidemic suggest that community perceptions, social norms and cultural practices can impede COVID-19 containment. To understand social responses towards COVID-19, the study aims to explore the understanding of COVID-19 and the acceptance of control measures among community members.MethodsWe conducted an exploratory qualitative study using a purposive sampling approach, at two communities of Karachi, Pakistan. In-depth interviews were conducted with community members including, young, middle-aged and older adults of both genders. Study data were analysed manually using the conventional content analysis technique.ResultsA total of 27 in-depth virtual interviews were conducted, between May and June 2020. Six overarching themes were identified: (1) community knowledge and perceptions around COVID-19; (2) trusted and preferred sources of health information; (3) initial thoughts and feeling towards COVID-19 pandemic; (4) community practices to prevent exposure from COVID-19; (5) perceived risks associated with poor adherence to infection control practices; and (6) future preparedness of community to avoid the second wave of the outbreak. Generally, community members had good knowledge about COVID-19, and positive behaviour and attitude towards using standard precautions. The knowledge is mainly acquired through electronic, print and social media platforms, which have pros and cons. However, some community members including younger individuals had poor adherence to safety measures. This may necessitate concentrated efforts to raise awareness through community mobilisation and sensitisation activities.ConclusionThis study provides an initial evidence base of communities' perceptions, and attitudes towards COVID-19 in an early stage of pandemic. The study emphasises that sufficient knowledge and awareness about COVID-19, adequate training and drills, and adherence to safety measures, are necessary to better prepare for the second wave of COVID-19.

Project description:ObjectiveTo explore healthcare provider's perspectives and experiences of the barriers and facilitators to treat and manage COVID-19 cases.Design and settingWe conducted an exploratory qualitative study using a purposive sampling approach, at a private tertiary care teaching hospital in Karachi, Pakistan. Study data were analysed manually using the conventional content analysis technique.ParticipantsKey-informant interviews (KIIs) were conducted with senior management and hospital leadership and in-depth interviews (IDIs) were conducted with front-line healthcare providers.ResultsA total of 31 interviews (KIIs=19; IDIs=12) were conducted, between April and May 2020. Three overarching themes emerged. The first was 'challenges faced by front-line healthcare providers working in COVID-19 wards. Healthcare workers experienced increased anxiety due to the fear of acquiring infection and transmitting it to their family members. They felt overwhelmed due to the exhaustive donning and doffing process, intense work and stigmatisation. The second theme was 'enablers supporting healthcare providers to deal with the COVID-19 pandemic'. Front liners pointed out several enabling factors that supported hospital staff including a safe hospital environment, adequate training, a strong system of information sharing and supportive management. The third theme was 'recommendations to support the healthcare workforce during the COVID-19 crisis'. Healthcare workers recommended measures to mitigate current challenges including providing risk allowance to front-line healthcare providers, preparing a backup health workforce, and establishing a platform to address the mental health needs of the healthcare providers.ConclusionThis study provides an initial evidence base of healthcare providers' experiences of managing patients with COVID-19 in the early stage of the pandemic and highlights measures needed to address the encountered challenges. It offers lessons for hospitals in low-income and middle-income countries to ensure a safe working environment for front-line workers in their fight against COVID-19.

Project description:Introduction Coronavirus disease 2019 (COVID-19) has become a global threat to public health. The current study investigates alterations in the biological estimates concerning the severity, recovery, mortality, and assessment of treatment-based outcomes. Methods A case series of 165 COVID-19 patients admitted to OMI Institute (a tertiary care hospital) was conducted between May and August 2020. The data regarding demographic characteristics, comorbid conditions, radiographic abnormalities, biological estimations, symptoms, treatment, disease progression, complications, and outcomes were recorded using a structured questionnaire. Laboratory estimations included complete blood count (CBC), renal and electrolyte profile, liver function tests (LFTs), hematological indices, and inflammatory markers. Chest X-ray, electrocardiogram (ECG), and a high-resolution computed tomography (HRCT) scan were also performed, and data were extracted from the medical records. Analysis was done using the Statistical Package for the Social Sciences (SPSS) version 22.0. Results Out of the 165 COVID-19 patients, 79.4% recovered and were successfully discharged, while 20.6% of inpatient died. The patients' mean age was 56.03 ± 15.96 years, with a male majority (55.1%). The most common comorbid conditions were diabetes and hypertension; fever and dry cough were among the most frequently reported symptoms. The chest imaging findings among the severe/critical COVID-19 patients showed extensive bilateral patchy opacities. The median laboratory investigations, including neutrophil-to-lymphocyte ratio (NLR) (14.83), C-reactive protein (CRP) (7.4 mg/dl), lactate dehydrogenase (LDH) (786 IU/L), ferritin (1401.15 mcg/ml), and mean oxygen saturation (88.25%), were significantly altered among cases with increased disease severity and those who expired (p<0.05). The proportion of acute respiratory distress syndrome (ARDS) and sepsis development was significantly high among severe/critical COVID-19 patients (p<0.05). Treatment with tocilizumab, remdesivir, doxycycline, ivermectin, enoxaparin sodium, and steroids was deemed to be potentially effective treatment options in terms of reducing COVID-19 severity and chances of recovery. Furthermore, age (OR 1.05; p=0.047), presence of comorbidity (OR 8.471; p=0.004), high NLR, LDH (final outcome) (OR 1.361 and 1.018; p<0.05), and CRP levels (midpoint) (OR 1.631; p=0.05) were identified as the strong predictors of death among COVID-19 patients. Conclusion The study identified several alterations in the clinical profile of the COVID-19 patients concerning severity during the hospital stay, affecting prognosis. Clinically, tocilizumab, remdesivir, doxycycline, ivermectin, enoxaparin sodium, and steroids were identified as potential therapeutic options for COVID-19 due to their ability to alter disease-associated severity and recovery rate.

Project description:ObjectivesForecasting epidemics like COVID-19 is of crucial importance, it will not only help the governments but also, the medical practitioners to know the future trajectory of the spread, which might help them with the best possible treatments, precautionary measures and protections. In this study, the popular autoregressive integrated moving average (ARIMA) will be used to forecast the cumulative number of confirmed, recovered cases, and the number of deaths in Pakistan from COVID-19 spanning June 25, 2020 to July 04, 2020 (10 days ahead forecast).MethodsTo meet the desire objectives, data for this study have been taken from the Ministry of National Health Service of Pakistan's website from February 27, 2020 to June 24, 2020. Two different ARIMA models will be used to obtain the next 10 days ahead point and 95% interval forecast of the cumulative confirmed cases, recovered cases, and deaths. Statistical software, RStudio, with "forecast", "ggplot2", "tseries", and "seasonal" packages have been used for data analysis.ResultsThe forecasted cumulative confirmed cases, recovered, and the number of deaths up to July 04, 2020 are 231239 with a 95% prediction interval of (219648, 242832), 111616 with a prediction interval of (101063, 122168), and 5043 with a 95% prediction interval of (4791, 5295) respectively. Statistical measures i.e. root mean square error (RMSE) and mean absolute error (MAE) are used for model accuracy. It is evident from the analysis results that the ARIMA and seasonal ARIMA model is better than the other time series models in terms of forecasting accuracy and hence recommended to be used for forecasting epidemics like COVID-19.ConclusionIt is concluded from this study that the forecasting accuracy of ARIMA models in terms of RMSE, and MAE are better than the other time series models, and therefore could be considered a good forecasting tool in forecasting the spread, recoveries, and deaths from the current outbreak of COVID-19. Besides, this study can also help the decision-makers in developing short-term strategies with regards to the current number of disease occurrences until an appropriate medication is developed.

Project description:BACKGROUND: Secondary infertility in developing countries is mostly attributable to blockage of the fallopian tubes due to adhesions caused by reproductive tract infections. There is a dearth of information on the prevalence and causes of secondary infertility from Pakistan. This paper presents results on factors associated with secondary infertility among married women in Karachi, Pakistan. METHODS: A matched case-control study was conducted. Cases were women aged 15-35 years with history of at least one previous conception and currently seeking treatment for secondary infertility. Controls were women residing in the neighborhood of cases with at least one live birth and not taking treatment for secondary infertility. The age of controls was matched by ±5 years to that of cases. Data was collected from June to August 2003. Conditional logistic regression was used to determine crude and adjusted odds ratios (OR) with corresponding 95% confidence intervals (CI) for factors associated with secondary infertility. RESULTS: The final multivariate logistic regression model revealed that after adjusting for age, cases were more likely to be the housewives (AOR = 2.6, 95% CI:1.5-4.4), had used inappropriate material to absorb blood during menstruation (AOR = 9.0, 95% CI: 5.0-16.4), and at their last delivery, had a birth attendant who did not wash hands with soap and water (AOR = 3.0, 95% CI: 1.4-5.7). Moreover, women with secondary infertility were more likely to report current or past history of having STI symptoms (AOR = 3.6, 95% CI: 2.4-5.6) and use of intra-vaginal indigenous medicines during their last post-partum period (AOR = 3.1, 95% CI: 1.6-5.7). CONCLUSION: We recommend health education and awareness messages for safe practices during menstruation, delivery, and the postpartum period for women in general. Additionally, sanitary napkins should be made available at an affordable cost, and safe delivery kits should contain educational/pictorial brochures for appropriate hand washing skills.