Author
Inaamul Haq
Other affiliations: Mamata Medical College, GMC, Government Medical College, Thiruvananthapuram ...read more
Bio: Inaamul Haq is an academic researcher from Government Medical College, Srinagar. The author has contributed to research in topics: Population & Seroprevalence. The author has an hindex of 13, co-authored 59 publications receiving 606 citations. Previous affiliations of Inaamul Haq include Mamata Medical College & GMC.
Topics: Population, Seroprevalence, Medicine, Dog bite, Cross-sectional study
Papers
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Indian Council of Medical Research1, All India Institute of Medical Sciences2, Regional Medical Research Centre3, Government Medical College, Srinagar4, Rajendra Memorial Research Institute of Medical Sciences5, Government of Karnataka6, National Institute of Occupational Health7, National Institute of Virology8, National Tuberculosis Institute9, National Centre for Disease Control10
TL;DR: Seroprevalence of SARS-CoV-2 was low among the adult population in India around the beginning of May 2020, and males, living in urban slums and occupation with high risk of exposure to potentially infected persons were associated with seropositivity.
Abstract: Background & objectives: Population-based seroepidemiological studies measure the extent of SARS-CoV-2 infection in a country. We report the findings of the first round of a national serosurvey, conducted to estimate the seroprevalence of SARS-CoV-2 infection among adult population of India. Methods: From May 11 to June 4, 2020, a randomly sampled, community-based survey was conducted in 700 villages/wards, selected from the 70 districts of the 21 States of India, categorized into four strata based on the incidence of reported COVID-19 cases. Four hundred adults per district were enrolled from 10 clusters with one adult per household. Serum samples were tested for IgG antibodies using COVID Kavach ELISA kit. All positive serum samples were re-tested using Euroimmun SARS-CoV-2 ELISA. Adjusting for survey design and serial test performance, weighted seroprevalence, number of infections, infection to case ratio (ICR) and infection fatality ratio (IFR) were calculated. Logistic regression was used to determine the factors associated with IgG positivity. Results: Total of 30,283 households were visited and 28,000 individuals were enrolled. Population-weighted seroprevalence after adjusting for test performance was 0.73 per cent [95% confidence interval (CI): 0.34-1.13]. Males, living in urban slums and occupation with high risk of exposure to potentially infected persons were associated with seropositivity. A cumulative 6,468,388 adult infections (95% CI: 3,829,029-11,199,423) were estimated in India by the early May. The overall ICR was between 81.6 (95% CI: 48.3-141.4) and 130.1 (95% CI: 77.0-225.2) with May 11 and May 3, 2020 as plausible reference points for reported cases. The IFR in the surveyed districts from high stratum, where death reporting was more robust, was 11.72 (95% CI: 7.21-19.19) to 15.04 (9.26-24.62) per 10,000 adults, using May 24 and June 1, 2020 as plausible reference points for reported deaths. Interpretation & conclusions: Seroprevalence of SARS-CoV-2 was low among the adult population in India around the beginning of May 2020. Further national and local serosurveys are recommended to better inform the public health strategy for containment and mitigation of the epidemic in various parts of the country.
171 citations
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Indian Council of Medical Research1, National Institute of Occupational Health2, Regional Medical Research Centre3, Government Medical College, Srinagar4, National Institute of Nutrition, Hyderabad5, Rajendra Memorial Research Institute of Medical Sciences6, National Tuberculosis Institute7, Government of Karnataka8
TL;DR: A second household serosurvey among individuals aged 10 years or older in the same 700 villages or wards within 70 districts in India that were included in the first sero-survey was conducted in this article.
143 citations
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TL;DR: A third serosurvey was conducted between December 2020 and January 2021 to estimate the seroprevalence of SARS-CoV-2 infection among the general population and healthcare workers (HCWs) in India as mentioned in this paper.
89 citations
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TL;DR: Both PSI and CURB-65 were found to have equal sensitivity to predict death from CAP and PSI was more sensitive in predicting ICU admission than CURb-65, while Specificity of CURBs65 was higher than that of PSI.
Abstract: Background. Little information is available from India regarding prognostic factors in patients with community acquired pneumonia (CAP). Methods. Hospital-based prospective study to test the validity of pneumonia severity index (PSI) and the confusion, urea, respiratory rate, blood pressure, age over 65 years (CURB-65) risk scoring systems in patients with CAP (n=150). Results. Although both CURB-65 class ≥III and PSI class ≥IV were 100% sensitive in predicting death, CURB-65 class ≥III had a higher specificity (74.6%) than PSI class ≥IV (52.2%) when used to predict death. In both PSI and CURB-65 risk scoring systems, mortality rate, need for intensive care unit (ICU) admission, prolonged need for intravenous (I.V.) antibiotics, prolonged duration of hospital stay and need for admission to ICU increased progressively with increasing scores. The PSI class ≥IV was more sensitive in predicting ICU admission than CURB-65. The duration of hospital stay was found to have a weak but significant correlation with PSI and CURB-65 criteria. Defervescence time also had a very weak but significant correlation with PSI and CURB-65 criteria. Duration of I.V. antibiotics had a moderately strong correlation with CURB-65 criteria but a weak correlation with PSI criteria. Conclusions. Both PSI and CURB-65 were found to have equal sensitivity to predict death from CAP. Specificity of CURB65 was higher than that of PSI. However, PSI was more sensitive in predicting ICU admission than CURB-65. [Indian J Chest Dis Allied Sci 2010;52:9-17]
68 citations
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Indian Council of Medical Research1, World Health Organization2, National Institute of Occupational Health3, Regional Medical Research Centre4, Government Medical College, Srinagar5, National Institute of Nutrition, Hyderabad6, Rajendra Memorial Research Institute of Medical Sciences7, National Tuberculosis Institute8, Government of India9
TL;DR: Nearly one in four individuals aged 10 years or older from general population as well as HCWs were exposed to SARS-CoV-2 by December 2020 amounting to 271 million infections in India.
Abstract: Background: Repeated cross-sectional serosurveys in the same geographic area establish the trend of the evolving pandemic. We present the findings of the third round of a national serosurvey to estimate the seroprevalence of SARS-CoV-2 infection among the general population and health care workers of India.
Methods: We conducted the third population-based serosurvey between Dec 18, 2020 and Jan 6, 2021 in the same 700 villages or wards from 70 districts in 21 states across India, which were selected for the first and second serosurveys. We enrolled from each district, at least 400 individuals aged ≥ 10 years from general population and 100 HCWs from sub-district level public health facilities. Serum samples from general population were tested for the presence of IgG antibodies against nucleocapsid (N) and spike protein (S1-RBD) of SARS-CoV-2 using the Abbott and Siemens assays respectively, whereas sera from HCWs were tested for anti-S1-RBD. For general population, sera positive for either of the antibodies were considered positive, while sera positive for anti-S1-RBD were considered as positive for HCW. Weighted seroprevalence estimates were adjusted for sensitivity and specificity of respective assays.
Findings: Of the 28,598 sera from general population, 4585 (16%) had IgG antibodies against N, 6647 (23.2%) against S1-RBD and 7436 (26%) against either. The weighted and assay characteristic adjusted seroprevalence against either of the antibodies was 24.1 (95%CI: 23.0% to 25.3%). Seroprevalence was lower in rural areas (21.4%, 95% CI: 20.3% to 22.6%) compared to urban non-slum (29.4%, 95% CI: 26.9% - 32.1%) and slum areas (34.6%, 95% CI: 31.0% to 38.3%). Among 7385 HCWs, the seroprevalence of anti-S1-RBD IgG antibodies was 25.6% (95% CI: 23.5% to 27.8%).
Interpretation: Nearly one in four individuals aged 10 years or older from general population as well as HCWs were exposed to SARS-CoV-2 by December 2020 amounting to 271 million infections in India.
Funding Statement: Indian Council of Medical Research
Declaration of Interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare no competing interests
Ethics Approval Statement: The project was approved by Institutional Human Ethics Committee at ICMR-National Institute of Epidemiology.
58 citations
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TL;DR: A deep learning (DL) based segmentation system is developed to automatically quantify infection regions of interest (ROIs) and their volumetric ratios w.r.t. the lung and possible applications, including but not limited to analysis of follow-up CT scans and infection distributions in the lobes and segments correlated with clinical findings were discussed.
Abstract: CT imaging is crucial for diagnosis, assessment and staging COVID-19 infection. Follow-up scans every 3-5 days are often recommended for disease progression. It has been reported that bilateral and peripheral ground glass opacification (GGO) with or without consolidation are predominant CT findings in COVID-19 patients. However, due to lack of computerized quantification tools, only qualitative impression and rough description of infected areas are currently used in radiological reports. In this paper, a deep learning (DL)-based segmentation system is developed to automatically quantify infection regions of interest (ROIs) and their volumetric ratios w.r.t. the lung. The performance of the system was evaluated by comparing the automatically segmented infection regions with the manually-delineated ones on 300 chest CT scans of 300 COVID-19 patients. For fast manual delineation of training samples and possible manual intervention of automatic results, a human-in-the-loop (HITL) strategy has been adopted to assist radiologists for infection region segmentation, which dramatically reduced the total segmentation time to 4 minutes after 3 iterations of model updating. The average Dice simiarility coefficient showed 91.6% agreement between automatic and manual infaction segmentations, and the mean estimation error of percentage of infection (POI) was 0.3% for the whole lung. Finally, possible applications, including but not limited to analysis of follow-up CT scans and infection distributions in the lobes and segments correlated with clinical findings, were discussed.
546 citations
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TL;DR: This poster discusses the management of Hypoxaemia and Cardiac arrhythmias with a focus on the treatment of the former and the importance of knowing the signs and symptoms of the latter.
Abstract: ### Monitoring, precautions and complications
### Hypoxaemia
### Cardiac arrhythmias
### Bleeding complications
541 citations
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TL;DR: Dr Benjamin A H Jensen Dr Aarabi Dr Mera A Ababneh Dr Albert Abaka-Yawson Dr Mohamed Salah Abassi Dr Getahun Abate Dr Tarek Mohamed Abd ElAziz Dr Rehab M Abd El-Baky Dr Amir Abdoli Dr Akebe Luther King Abia Dr Fatma Ben Abid Prof Dr Khaled M Aboshanab Mr Ashenafi Abossie Dr Abouelfetouh Dr Maja Abram
Abstract: Dr Benjamin A H Jensen Dr Aarabi Dr Mera A Ababneh Dr Albert Abaka-Yawson Dr Mohamed Salah Abassi Dr Getahun Abate Dr Tarek Mohamed Abd ElAziz Dr Rehab M Abd El-Baky Dr Amir Abdoli Dr Akebe Luther King Abia Dr Fatma Ben Abid Prof Dr Khaled M Aboshanab Mr Ashenafi Abossie Dr Abouelfetouh Dr Maja Abram Dr Sawsan Abuhammad Dr Abulebda Professor Ali Acar Mr Oliver Okoth Achila Dr Stefan Acosta Dr Azeez Adeboye Dr Sanjib Adhikari Prof Dr Muhammad Sohail Afzal Dr Fabio Aguiar-Alves Dr Thomas Agyarko-Poku Dr Irfan Ahmad Dr Suhail Ahmad Dr Hafiz Ahmad Dr Elham Ahmadi Dr Zahra Ahmadinejad Dr Ehsan Ahmadpour Dr Haroon Ahmed Dr Firoz Ahmed Dr Wan M Aizat Dr Abraham Ajayi Dr Ali Akbar Dr Sami Akbulut Dr Hashaam Akhtar Professor Ala-Eddin Al Moustafa Dr Al-Hasan Dr Ali Al-Jumaili Dr Alexandre Alanio Dr Eliana Alcaraz Dr Maria D Alcantar Curiel Dr Gaetano Alfano Prof Dr Abdelazeem Algammal Dr Iftikhar Ali Dr Musa Mohammed Ali Dr Ihsan Ali Dr Mohammad Javed Ali Dr Ali Muhsin Ali Dr Shahzad Ali Dr Sheikh Alif Professor Michael Alifrangis Dr Reem Aljindan Prof Dr Karel Allegaert Dr Rosalie Allison Dr Ammar Almaaytah Dr Dhary Alewy Almashhadany Dr Tarig Alnour Dr Bandar Alosaimi Mr Abdullah Alqarihi Dr Alian A Alrasheedy Dr Eduardo Amaral Dr Gul Ambreen Professor Gobena Ameni Dr Ahmed Ammar Dr Linda Amoah Professor Luca Ampollini Dr Edina Amponsah-Dacosta Dr Mirko Ancillotti Ms Motswedi Anderson Dr Angel Andrade Dr Sergio Angel Dr Angkasekwinai Dr Archana Angrup Dr Enoch Aninagyei Dr Shamshul Ansari Dr Beena Antony Dr Nopporn Apiwattanakul Dr Amjad Islam Aqib Professor Mohammad Arabestani Dr Sheila Araujo Teles Dr Balew Arega Dr Gunjan Arora Dr Muhammad Imran Arshad Dr Yasir Arshad Dr Kovy Arteaga-Livias Dr Mohd Hafiz Arzmi Dr Mohammad Reza Asadi Karam Dr Takanori Asakura Dr Prince Asare Dr Mohammad Asgharzadeh Dr Hossam Ashour Dr Abdullah Tarik Aslan Dr Alaa Atamna Dr Nur Atik Dr Meiji Soe Aung Dr Wah Wah Aung Professor Sergey Avdeev Dr Akshay Avula Dr Babafela Awosile Dr Gajendra Kumar Azad Dr Davood Azadi Mr Zelalem Nigussie Azene Dr Afzal Azim Mr Muhammad Majid Aziz Dr Martin Sima Dr Azer Ozad Duzgun Dr Kenan Cetin Dr Aysegul Copur Cicek Dr Ines Bado Dr Fang Bai Dr J Kevin Baird Dr Andrea Ballini Prof Dr Zulqarnain Baloch Dr Joseph Baruch Baluku Dr Banaei Prof Dr Tuhina Banerjee Dr Tuhina Banerjee Mr Agegnehu Bante Dr Humberto Barrios Camacho Dr Mazin Barry Dr Bruno Barsic Dr Christopher S von Bartheld Dr Dariusz Bartosik Dr Joseph Baruch Baluku Dr Rasha Barwa Dr Saurav Basu Dr George Bayliss
420 citations
01 Jan 2014
378 citations