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Article ; Online: Association of air pollution and weather conditions during infection course with COVID-19 case fatality rate in the United Kingdom.

Hossain, M Pear / Zhou, Wen / Leung, Marco Y T / Yuan, Hsiang-Yu

2024 Volume 14, Issue 1, Page(s) 683

Abstract: ... days after (OR 1.24; 95% CI 1.18-1.30) and increased [Formula: see text] (19 μg/m ...

Abstract	Although the relationship between the environmental factors, such as weather conditions and air pollution, and COVID-19 case fatality rate (CFR) has been found, the impacts of these factors to which infected cases are exposed at different infectious stages (e.g., virus exposure time, incubation period, and at or after symptom onset) are still unknown. Understanding this link can help reduce mortality rates. During the first wave of COVID-19 in the United Kingdom (UK), the CFR varied widely between and among the four countries of the UK, allowing such differential impacts to be assessed. We developed a generalized linear mixed-effect model combined with distributed lag nonlinear models to estimate the odds ratio of the weather factors (i.e., temperature, sunlight, relative humidity, and rainfall) and air pollution (i.e., ozone, [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text]) using data between March 26, 2020 and September 15, 2020 in the UK. After retrospectively time adjusted CFR was estimated using back-projection technique, the stepwise model selection method was used to choose the best model based on Akaike information criteria and the closeness between the predicted and observed values of CFR. The risk of death reached its maximum level when the low temperature (6 °C) occurred 1 day before (OR 1.59; 95% CI 1.52-1.63), prolonged sunlight duration (11-14 h) 3 days after (OR 1.24; 95% CI 1.18-1.30) and increased [Formula: see text] (19 μg/m
MeSH term(s)	Humans ; Retrospective Studies ; COVID-19/epidemiology ; Weather ; Air Pollution/adverse effects ; United Kingdom/epidemiology
Language	English
Publishing date	2024-01-06
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-50474-w
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Association of air pollution and weather conditions during infection course with COVID-19 case fatality rate in the United Kingdom

M. Pear Hossain / Wen Zhou / Marco Y. T. Leung / Hsiang-Yu Yuan

Scientific Reports, Vol 14, Iss 1, Pp 1-

2024 Volume 10

Abstract: ... ozone, $$N{O}_{2}$$ N O 2 , $$S{O}_{2}$$ S O 2 , $$CO$$ CO , $$P{M}_{10}$$ P M 10 and $$P{M}_{2.5}$$ P M ... 24; 95% CI 1.18–1.30) and increased $$P{M}_{2.5}$$ P M 2.5 (19 μg/m3) 1 day after the onset ...

Abstract	Abstract Although the relationship between the environmental factors, such as weather conditions and air pollution, and COVID-19 case fatality rate (CFR) has been found, the impacts of these factors to which infected cases are exposed at different infectious stages (e.g., virus exposure time, incubation period, and at or after symptom onset) are still unknown. Understanding this link can help reduce mortality rates. During the first wave of COVID-19 in the United Kingdom (UK), the CFR varied widely between and among the four countries of the UK, allowing such differential impacts to be assessed. We developed a generalized linear mixed-effect model combined with distributed lag nonlinear models to estimate the odds ratio of the weather factors (i.e., temperature, sunlight, relative humidity, and rainfall) and air pollution (i.e., ozone, $$N{O}_{2}$$ N O 2 , $$S{O}_{2}$$ S O 2 , $$CO$$ CO , $$P{M}_{10}$$ P M 10 and $$P{M}_{2.5}$$ P M 2.5 ) using data between March 26, 2020 and September 15, 2020 in the UK. After retrospectively time adjusted CFR was estimated using back-projection technique, the stepwise model selection method was used to choose the best model based on Akaike information criteria and the closeness between the predicted and observed values of CFR. The risk of death reached its maximum level when the low temperature (6 °C) occurred 1 day before (OR 1.59; 95% CI 1.52–1.63), prolonged sunlight duration (11–14 h) 3 days after (OR 1.24; 95% CI 1.18–1.30) and increased $$P{M}_{2.5}$$ P M 2.5 (19 μg/m3) 1 day after the onset of symptom (OR 1.12; 95% CI 1.09–1.16). After reopening, many COVID-19 cases will be identified after their symptoms appear. The findings highlight the importance of designing different preventive measures against severe illness or death considering the time before and after symptom onset.
Keywords	Medicine ; R ; Science ; Q
Subject code	333
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Assessment of the fatality rate and transmissibility taking account of undetected cases during an unprecedented COVID-19 surge in Taiwan.

Yuan, Hsiang-Yu / Hossain, M Pear / Wen, Tzai-Hung / Wang, Ming-Jiuh

BMC infectious diseases

2022 Volume 22, Issue 1, Page(s) 271

Abstract: Background: During the COVID-19 outbreak in Taiwan between May 11 and June 20, 2021, the observed fatality rate (FR) was 5.3%, higher than the global average at 2.1%. The high number of reported deaths suggests that many patients were not treated ... ...

Abstract	Background: During the COVID-19 outbreak in Taiwan between May 11 and June 20, 2021, the observed fatality rate (FR) was 5.3%, higher than the global average at 2.1%. The high number of reported deaths suggests that many patients were not treated promptly or effectively. However, many unexplained deaths were subsequently identified as cases, indicating a few undetected cases, resulting in a higher estimate of FR. Whether the true FR is exceedingly high and what factors determine the detection of cases remain unknown. Estimating the true number of total infected cases (i.e. including undetected cases) can allow an accurate estimation of FR and effective reproduction number ([Formula: see text]). Methods: We aimed at quantifying the time-varying FR and [Formula: see text] using the estimated true numbers of cases; and, exploring the relationship between the true case number and test and trace data. After adjusting for reporting delays, we developed a model to estimate the number of undetected cases using reported deaths that were and were not previously detected. The daily FR and [Formula: see text] were calculated using the true number of cases. Afterwards, a logistic regression model was used to assess the impact of daily testing and tracing data on the detection ratio of deaths. Results: The estimated true daily case number at the peak of the outbreak on May 22 was 897, which was 24.3% higher than the reported number, but the difference became less than 4% on June 9 and afterwards. After taking account of undetected cases, our estimated mean FR (4.7%) was still high but the daily rate showed a large decrease from 6.5% on May 19 to 2.8% on June 6. [Formula: see text] reached a maximum value of 6.4 on May 11, compared to 6.0 estimated using the reported case number. The decreasing proportion of undetected cases was found to be associated with the increases in the ratio of the number of tests conducted to reported cases, and the proportion of cases that are contact traced before symptom onset. Conclusions: Increasing testing capacity and contact tracing coverage without delays not only improve parameter estimation by reducing hidden cases but may also reduce fatality rates.
MeSH term(s)	Basic Reproduction Number ; COVID-19/epidemiology ; Humans ; Taiwan/epidemiology
Language	English
Publishing date	2022-03-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2041550-3
ISSN	1471-2334 ; 1471-2334
ISSN (online)	1471-2334
ISSN	1471-2334
DOI	10.1186/s12879-022-07190-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Association between PM2.5 air pollution, temperature, and sunlight during different infectious stages with the case fatality of COVID-19 in the United Kingdom: a modeling study

Hossain, M. Pear / Zhou, Wen / Leung, Marco Y. T. / Yuan, Hsiang-Yu

medRxiv

Abstract: ... increased PM_2.5 (11-18μg/m³) after the incubation period posed a greater risk of death ...

Abstract	Although the relationship between the environmental factors such as weather conditions and air pollution and COVID-19 case fatality rate (CFR) has been found, the impacts of these factors to which infected cases are exposed at different infectious stages (e.g., virus exposure time, incubation period, and at or after symptom onset) are still unknown. Understanding this link can help reduce mortality rates. During the first wave of COVID-19 in the United Kingdom (UK), the CFR varied widely between and among the four countries of the UK, allowing such differential impacts to be assessed. We developed a generalized linear mixed-effect model combined with distributed lag nonlinear models to estimate the odds ratio of the weather factors (i.e., temperature, sunlight, relative humidity, and rainfall) and air pollution (i.e., ozone, NO<sub>2</sub>, SO<sub>2</sub>, CO, PM<sub>10</sub> and PM<sub>2.5</sub>) using data between March 26, 2020 and May 12, 2020 in the UK. After retrospectively time adjusted CFR was estimated using back-projection technique, the stepwise model selection method was used to choose the best model based on Akaike information criteria (AIC) and the closeness between the predicted and observed values of CFR. We found that the low temperature (8-11<sup>∘</sup>; C), prolonged sunlight duration (11-13hours) and increased PM<sub>2.5</sub> (11-18μg/m<sup>3</sup>) after the incubation period posed a greater risk of death (measured by odds ratio (OR)) than the earlier infectious stages. The risk reached its maximum level when the low temperature occurred one day after (OR = 1.76; 95% CI: 1.10-2.81), prolonged sunlight duration 2-3 days after (OR = 1.50; 95% CI: 1.03-2.18) and increased PM<sub>2.5</sub> at the onset of symptom (OR =1.72; 95% CI: 1.30-2.26). In contrast, prolonged sunlight duration showed a protective effect during the incubation period or earlier. After reopening, many COVID-19 cases will be identified after their symptoms appear. The findings highlight the importance of designing different preventive measures against severe illness or death considering the time before and after symptom onset.
Keywords	covid19
Language	English
Publishing date	2023-04-09
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2023.04.07.23288300
Database	COVID19

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Article ; Online: Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018.

M Pear Hossain / Wen Zhou / Chao Ren / John Marshall / Hsiang-Yu Yuan

PLOS Global Public Health, Vol 2, Iss 5, p e

2022 Volume 0000047

Abstract: The incidence of dengue has increased rapidly in Bangladesh since 2010 with an outbreak in 2018 reaching a historically high number of cases, 10,148. A better understanding of the effects of climate variability before dengue season on the increasing ... ...

Abstract	The incidence of dengue has increased rapidly in Bangladesh since 2010 with an outbreak in 2018 reaching a historically high number of cases, 10,148. A better understanding of the effects of climate variability before dengue season on the increasing incidence of dengue in Bangladesh can enable early warning of future outbreaks. We developed a generalized linear model to predict the number of annual dengue cases based on monthly minimum temperature, rainfall and sunshine prior to dengue season. Variable selection and leave-one-out cross-validation were performed to identify the best prediction model and to evaluate the model's performance. Our model successfully predicted the largest outbreak in 2018, with 10,077 cases (95% CI: [9,912-10,276]), in addition to smaller outbreaks in five different years (2003, 2006, 2010, 2012 and 2014) and successfully identified the increasing trend in cases between 2010 and 2018. We found that temperature was positively associated with the annual incidence during the late winter months (between January and March) but negatively associated during the early summer (between April and June). Our results might be suggest an optimal minimum temperature for mosquito growth of 21-23°C. This study has implications for understanding how climate variability has affected recent dengue expansion in neighbours of Bangladesh (such as northern India and Southeast Asia).
Keywords	Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018.

Hossain, M Pear / Zhou, Wen / Ren, Chao / Marshall, John / Yuan, Hsiang-Yu

PLOS global public health

2022 Volume 2, Issue 5, Page(s) e0000047

Abstract	The incidence of dengue has increased rapidly in Bangladesh since 2010 with an outbreak in 2018 reaching a historically high number of cases, 10,148. A better understanding of the effects of climate variability before dengue season on the increasing incidence of dengue in Bangladesh can enable early warning of future outbreaks. We developed a generalized linear model to predict the number of annual dengue cases based on monthly minimum temperature, rainfall and sunshine prior to dengue season. Variable selection and leave-one-out cross-validation were performed to identify the best prediction model and to evaluate the model's performance. Our model successfully predicted the largest outbreak in 2018, with 10,077 cases (95% CI: [9,912-10,276]), in addition to smaller outbreaks in five different years (2003, 2006, 2010, 2012 and 2014) and successfully identified the increasing trend in cases between 2010 and 2018. We found that temperature was positively associated with the annual incidence during the late winter months (between January and March) but negatively associated during the early summer (between April and June). Our results might be suggest an optimal minimum temperature for mosquito growth of 21-23°C. This study has implications for understanding how climate variability has affected recent dengue expansion in neighbours of Bangladesh (such as northern India and Southeast Asia).
Language	English
Publishing date	2022-05-09
Publishing country	United States
Document type	Journal Article
ISSN	2767-3375
ISSN (online)	2767-3375
DOI	10.1371/journal.pgph.0000047
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Job insecurity and mental health related outcomes among the humanitarian workers during COVID-19 pandemic: a cross-sectional study.

Sultana, Naznin / Asaduzzaman, Md / Siddique, Abu Bakkar / Khatun, Hafeza / Bari, Farzana Sultana / Islam, Md Nazrul / Tabassum, Arifa / Mondol, Abdus Salam / Sayem, Md Abu / Abdullah, Abu Yousuf Md / Hossain, M Pear / Biracyaza, Emmanuel

BMC psychology

2022 Volume 10, Issue 1, Page(s) 265

Abstract: Background: The COVID-19 remains a public health burden that has caused global economic crises, jeopardizing health, jobs, and livelihoods of millions of people around the globe. Several efforts have been made by several countries by implementing ... ...

Abstract	Background: The COVID-19 remains a public health burden that has caused global economic crises, jeopardizing health, jobs, and livelihoods of millions of people around the globe. Several efforts have been made by several countries by implementing several health strategies to attenuate the spread of the pandemic. Although several studies indicated effects of COVID-19 on mental health and its associated factors, very little is known about the underlying mechanism of job insecurity, depression, anxiety, and stress in Bangladesh. Therefore, this study determined the prevalence of job insecurity and depression, anxiety, stress as well as the association between job insecurity, mental health outcomes also contributing determinants amongst humanitarian workers during the COVID-19 pandemic in Bangladesh. Methods: We conducted a web-based cross-sectional study among 445 humanitarian workers during the COVID-19 pandemic in six sub-districts of Cox's bazar district of Bangladesh between April and May 2021. The questionnaire was composed of socio-demographic, lifestyle and work related factors. Psychometric instruments like job insecurity scale and depression, anxiety also stress scale (DASS-21) were employed to assess the level of job insecurity and mental health outcomes (depression, anxiety and stress). STATA software version 14 was employed to perform statistical analyses. Results: The prevalence of job insecurity was 42%. The odds of job insecurity was higher in Kutubdia and Pekua (AOR = 3.1, 95% CI 1.36, 7.22) Teknaf (AOR = 2.9, 95% CI 1.33, 6.41), the impact of dissatisfaction on salary (AOR = 2.3, 95% CI 1.49, 3.58) was evident with job insecurity. The prevalence of moderate to severe depression, anxiety and stress among humanitarian worker were (26%, 7%), (25%, 10%) and (15%, 7%) respectively. Further, the region of work, being female, marital status, work environment, and salary dissatisfaction were contributing factors for poor mental health outcomes. Those with job insecurity were almost 3 times more likely to experience depression (AOR = 2.7, 95% CI 1.85, 4.04), anxiety (AOR = 2.6, 95% CI 1.76, 3.71) and stress (AOR: 2.8; 95% CI 1.89, 4.26), respectively. Conclusion: Our findings highlight that job security remains essential to help tackle the severity of depression, anxiety and stress in humanitarian workers. The results reflected the critical importance of local and international NGOs addressing poor mental health conditions of their employees to prevent mental health outbreaks.
MeSH term(s)	Female ; Humans ; Male ; COVID-19/epidemiology ; Pandemics ; Mental Health ; Cross-Sectional Studies ; Depression/epidemiology ; Depression/etiology ; Anxiety/epidemiology ; Anxiety/etiology ; Workplace
Language	English
Publishing date	2022-11-14
Publishing country	England
Document type	Journal Article
ZDB-ID	2705921-2
ISSN	2050-7283 ; 2050-7283
ISSN (online)	2050-7283
ISSN	2050-7283
DOI	10.1186/s40359-022-00974-7
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Article ; Online: The effects of border control and quarantine measures on the spread of COVID-19.

Hossain, M Pear / Junus, Alvin / Zhu, Xiaolin / Jia, Pengfei / Wen, Tzai-Hung / Pfeiffer, Dirk / Yuan, Hsiang-Yu

Epidemics

2020 Volume 32, Page(s) 100397

Abstract: 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 ... ...

Abstract	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 R
MeSH term(s)	Betacoronavirus ; COVID-19 ; China/epidemiology ; Communicable Disease Control/organization & administration ; Coronavirus Infections/epidemiology ; Coronavirus Infections/prevention & control ; Coronavirus Infections/transmission ; Humans ; Incidence ; Models, Statistical ; Pandemics/prevention & control ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/prevention & control ; Pneumonia, Viral/transmission ; SARS-CoV-2 ; Time Factors ; Travel
Keywords	covid19
Language	English
Publishing date	2020-06-06
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2467993-8
ISSN	1878-0067 ; 1755-4365
ISSN (online)	1878-0067
ISSN	1755-4365
DOI	10.1016/j.epidem.2020.100397
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Article ; Online: The effects of border control and quarantine measures on the spread of COVID-19

M. Pear Hossain / Alvin Junus / Xiaolin Zhu / Pengfei Jia / Tzai-Hung Wen / Dirk Pfeiffer / Hsiang-Yu Yuan

Epidemics, Vol 32, Iss , Pp 100397- (2020)

2020

Abstract	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 τ = 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.
Keywords	Infectious and parasitic diseases ; RC109-216 ; covid19
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The effects of border control and quarantine measures on global spread of COVID-19

Hossain, M. Pear / Junus, Alvin / Zhu, Xiaolin / Jia, Pengfei / Wen, Tzai-Hung / Pfeiffer, Dirk / Yuan, Hsiang-Yu

medRxiv

Keywords	covid19
Language	English
Publishing date	2020-03-17
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2020.03.13.20035261
Database	COVID19

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