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Article ; Online: Severity and outcomes of Omicron variant of SARS-CoV-2 compared to Delta variant and severity of Omicron sublineages

Lisa Askie / Maria D Van Kerkhove / Janet Diaz / Olivier Le Polain de Waroux / Nkengafac Villyen Motaze / Pryanka Relan / Bharath Kumar Tirupakuzhi Vijayaraghavan / Kavita Kothari

BMJ Global Health, Vol 8, Iss

a systematic review and metanalysis

2023 Volume 7

Abstract: Objectives To compare severity and clinical outcomes from Omicron as compared with the Delta variant and to compare outcomes between Omicron sublineages.Methods We searched the WHO COVID-19 Research database for studies that compared clinical outcomes ... ...

Abstract	Objectives To compare severity and clinical outcomes from Omicron as compared with the Delta variant and to compare outcomes between Omicron sublineages.Methods We searched the WHO COVID-19 Research database for studies that compared clinical outcomes for patients with Omicron variant and the Delta variant, and separately Omicron sublineages BA.1 and BA.2. A random-effects meta-analysis was used to pool estimates of relative risk (RR) between variants and sublineages. Heterogeneity between studies was assessed using the I2 index. Risk of bias was assessed using the tool developed by the Clinical Advances through Research and Information Translation team.Results Our search identified 1494 studies and 42 met the inclusion criteria. Eleven studies were published as preprints. Of the 42 studies, 29 adjusted for vaccination status; 12 had no adjustment; and for 1, the adjustment was unclear. Three of the included studies compared the sublineages of Omicron BA.1 versus BA.2. As compared with Delta, individuals infected with Omicron had 61% lower risk of death (RR 0.39, 95% CI 0.33 to 0.46) and 56% lower risk of hospitalisation (RR 0.44, 95% CI 0.34 to 0.56). Omicron was similarly associated with lower risk of intensive care unit (ICU) admission, oxygen therapy, and non-invasive and invasive ventilation. The pooled risk ratio for the outcome of hospitalisation when comparing sublineages BA.1 versus BA.2 was 0.55 (95% 0.23 to 1.30).Discussion Omicron variant was associated with lower risk of hospitalisation, ICU admission, oxygen therapy, ventilation and death as compared with Delta. There was no difference in the risk of hospitalisation between Omicron sublineages BA.1 and BA.2.PROSPERO registration number CRD42022310880.
Keywords	Medicine (General) ; R5-920 ; Infectious and parasitic diseases ; RC109-216
Subject code	610
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	BMJ Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Worldwide Reduction in MERS Cases and Deaths since 2016

Christl A. Donnelly / Mamun R. Malik / Amgad Elkholy / Simon Cauchemez / Maria D. Van Kerkhove

Emerging Infectious Diseases, Vol 25, Iss 9, Pp 1758-

2019 Volume 1760

Abstract: Since 2012, Middle East respiratory syndrome (MERS) coronavirus has infected 2,442 persons worldwide. Case-based data analysis suggests that since 2016, as many as 1,465 cases and 293–520 deaths might have been averted. Efforts to reduce the global MERS ... ...

Abstract	Since 2012, Middle East respiratory syndrome (MERS) coronavirus has infected 2,442 persons worldwide. Case-based data analysis suggests that since 2016, as many as 1,465 cases and 293–520 deaths might have been averted. Efforts to reduce the global MERS threat are working, but countries must maintain vigilance to prevent further infections.
Keywords	Medicine ; R ; Infectious and parasitic diseases ; RC109-216 ; covid19
Language	English
Publishing date	2019-09-01T00:00:00Z
Publisher	Centers for Disease Control and Prevention
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: MERS-CoV infection among healthcare workers and risk factors for death

Amgad A. Elkholy / Rebecca Grant / Abdullah Assiri / Mohamed Elhakim / Mamunur R. Malik / Maria D. Van Kerkhove

Journal of Infection and Public Health, Vol 13, Iss 3, Pp 418-

Retrospective analysis of all laboratory-confirmed cases reported to WHO from 2012 to 2 June 2018

2020 Volume 422

Abstract: Background: Approximately half of the reported laboratory-confirmed infections of Middle East respiratory syndrome coronavirus (MERS-CoV) have occurred in healthcare settings, and healthcare workers constitute over one third of all secondary infections. ... ...

Abstract	Background: Approximately half of the reported laboratory-confirmed infections of Middle East respiratory syndrome coronavirus (MERS-CoV) have occurred in healthcare settings, and healthcare workers constitute over one third of all secondary infections. This study aimed to describe secondary cases of MERS-CoV infection among healthcare workers and to identify risk factors for death. Methods: A retrospective analysis was conducted on epidemiological data of laboratory-confirmed MERS-CoV cases reported to the World Health Organization from September 2012 to 2 June 2018. We compared all secondary cases among healthcare workers with secondary cases among non-healthcare workers. Multivariable logistic regression identified risk factors for death. Results: Of the 2223 laboratory-confirmed MERS-CoV cases reported to WHO, 415 were healthcare workers and 1783 were non-healthcare workers. Compared with non-healthcare workers cases, healthcare workers cases were younger (P < 0.001), more likely to be female (P < 0.001), non-nationals (P < 0.001) and asymptomatic (P < 0.001), and have fewer comorbidities (P < 0.001) and higher rates of survival (P < 0.001). Year of infection (2013–2018) and having no comorbidities were independent protective factors against death among secondary healthcare workers cases. Conclusion: Being able to protect healthcare workers from high threat respiratory pathogens, such as MERS-CoV is important for being able to reduce secondary transmission of MERS-CoV in healthcare-associated outbreaks. By extension, reducing infection in healthcare workers improves continuity of care for all patients within healthcare facilities. Keywords: MERS-CoV, Nosocomial infection, Infection prevention and control
Keywords	Infectious and parasitic diseases ; RC109-216 ; Public aspects of medicine ; RA1-1270
Subject code	360
Language	English
Publishing date	2020-03-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Pharmacologic Treatments and Supportive Care for Middle East Respiratory Syndrome

Taylor Kain / Patrick J. Lindsay / Neill K.J. Adhikari / Yaseen M. Arabi / Maria D. Van Kerkhove / Robert A. Fowler

Emerging Infectious Diseases, Vol 26, Iss 6, Pp 1102-

2020 Volume 1112

Abstract: Available animal and cell line models have suggested that specific therapeutics might be effective in treating Middle East respiratory syndrome (MERS). We conducted a systematic review of evidence for treatment with pharmacologic and supportive therapies. ...

Abstract	Available animal and cell line models have suggested that specific therapeutics might be effective in treating Middle East respiratory syndrome (MERS). We conducted a systematic review of evidence for treatment with pharmacologic and supportive therapies. We developed a protocol and searched 5 databases for studies describing treatment of MERS and deaths in MERS patients. Risk of bias (RoB) was assessed by using ROBINS-I tool. We retrieved 3,660 unique citations; 20 observational studies met eligibility, and we studied 13 therapies. Most studies were at serious or critical RoB; no studies were at low RoB. One study, at moderate RoB, showed reduced mortality rates in severe MERS patients with extracorporeal membrane oxygenation; no other studies showed a significant lifesaving benefit to any treatment. The existing literature on treatments for MERS is observational and at moderate to critical RoB. Clinical trials are needed to guide treatment decisions.
Keywords	Middle East respiratory syndrome ; MERS ; coronavirus ; CoV ; coronavirus infections ; acute respiratory distress syndrome ; Medicine ; R ; Infectious and parasitic diseases ; RC109-216
Subject code	610
Language	English
Publishing date	2020-06-01T00:00:00Z
Publisher	Centers for Disease Control and Prevention
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Current challenges and implications for dengue, chikungunya and Zika seroprevalence studies worldwide

Camille Fritzell / Dominique Rousset / Antoine Adde / Mirdad Kazanji / Maria D Van Kerkhove / Claude Flamand

PLoS Neglected Tropical Diseases, Vol 12, Iss 7, p e

A scoping review.

2018 Volume 0006533

Abstract: BACKGROUND:Arboviral infections are a public health concern and an escalating problem worldwide. Estimating the burden of these diseases represents a major challenge that is complicated by the large number of unapparent infections, especially those of ... ...

Abstract	BACKGROUND:Arboviral infections are a public health concern and an escalating problem worldwide. Estimating the burden of these diseases represents a major challenge that is complicated by the large number of unapparent infections, especially those of dengue fever. Serological surveys are thus required to identify the distribution of these diseases and measure their impact. Therefore, we undertook a scoping review of the literature to describe and summarize epidemiological practices, findings and insights related to seroprevalence studies of dengue, chikungunya and Zika virus, which have rapidly expanded across the globe in recent years. METHODOLOGY/PRINCIPAL FINDINGS:Relevant studies were retrieved through a literature search of MEDLINE, WHOLIS, Lilacs, SciELO and Scopus (2000 to 2018). In total, 1389 publications were identified. Studies addressing the seroprevalence of dengue, chikungunya and/or Zika written in English or French and meeting the inclusion and exclusion criteria were included. In total, 147 studies were included, from which 185 data points were retrieved, as some studies used several different samples. Most of the studies were exclusively conducted on dengue (66.5%), but 16% were exclusively conducted on chikungunya, and 7 were exclusively conducted on Zika; the remainder were conducted on multiple arboviruses. A wide range of designs were applied, but most studies were conducted in the general population (39%) and in households (41%). Although several assays were used, enzyme-linked immunosorbent assays (ELISAs) were the predominant test used (77%). The temporal distribution of chikungunya studies followed the virus during its rapid expansion since 2004. The results revealed heterogeneity of arboviruses seroprevalence between continents and within a given country for dengue, chikungunya and Zika viruses, ranging from 0 to 100%, 76% and 73% respectively. CONCLUSIONS/SIGNIFICANCE:Serological surveys provide the most direct measurement for defining the immunity landscape for infectious diseases, ...
Keywords	Arctic medicine. Tropical medicine ; RC955-962 ; Public aspects of medicine ; RA1-1270
Subject code	001
Language	English
Publishing date	2018-07-01T00:00:00Z
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: Epidemic and intervention modelling

Maria D Van Kerkhove / Neil M Ferguson

Bulletin of the World Health Organization, Vol 90, Iss 4, Pp 306-

a scientific rationale for policy decisions? Lessons from the 2009 influenza pandemic

2012 Volume 310

Abstract: PROBLEM: Outbreak analysis and mathematical modelling are crucial for planning public health responses to infectious disease outbreaks, epidemics and pandemics. This paper describes the data analysis and mathematical modelling undertaken during and ... ...

Abstract	PROBLEM: Outbreak analysis and mathematical modelling are crucial for planning public health responses to infectious disease outbreaks, epidemics and pandemics. This paper describes the data analysis and mathematical modelling undertaken during and following the 2009 influenza pandemic, especially to inform public health planning and decision-making. APPROACH: Soon after A(H1N1)pdm09 emerged in North America in 2009, the World Health Organization convened an informal mathematical modelling network of public health and academic experts and modelling groups. This network and other modelling groups worked with policy-makers to characterize the dynamics and impact of the pandemic and assess the effectiveness of interventions in different settings. SETTING: The 2009 A(H1N1) influenza pandemic. RELEVANT CHANGES: Modellers provided a quantitative framework for analysing surveillance data and for understanding the dynamics of the epidemic and the impact of interventions. However, what most often informed policy decisions on a day-to-day basis was arguably not sophisticated simulation modelling, but rather, real-time statistical analyses based on mechanistic transmission models relying on available epidemiologic and virologic data. LESSONS LEARNT: A key lesson was that modelling cannot substitute for data; it can only make use of available data and highlight what additional data might best inform policy. Data gaps in 2009, especially from low-resource countries, made it difficult to evaluate severity, the effects of seasonal variation on transmission and the effectiveness of non-pharmaceutical interventions. Better communication between modellers and public health practitioners is needed to manage expectations, facilitate data sharing and interpretation and reduce inconsistency in results.
Keywords	Public aspects of medicine ; RA1-1270 ; Medicine ; R
Subject code	306
Language	English
Publishing date	2012-04-01T00:00:00Z
Publisher	World Health Organization
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Epidemic and intervention modelling

Maria D Van Kerkhove / Neil M Ferguson

Bulletin of the World Health Organization, Vol 90, Iss 4, Pp 306-

a scientific rationale for policy decisions? Lessons from the 2009 influenza pandemic

2012 Volume 310

Abstract	PROBLEM: Outbreak analysis and mathematical modelling are crucial for planning public health responses to infectious disease outbreaks, epidemics and pandemics. This paper describes the data analysis and mathematical modelling undertaken during and following the 2009 influenza pandemic, especially to inform public health planning and decision-making. APPROACH: Soon after A(H1N1)pdm09 emerged in North America in 2009, the World Health Organization convened an informal mathematical modelling network of public health and academic experts and modelling groups. This network and other modelling groups worked with policy-makers to characterize the dynamics and impact of the pandemic and assess the effectiveness of interventions in different settings. SETTING: The 2009 A(H1N1) influenza pandemic. RELEVANT CHANGES: Modellers provided a quantitative framework for analysing surveillance data and for understanding the dynamics of the epidemic and the impact of interventions. However, what most often informed policy decisions on a day-to-day basis was arguably not sophisticated simulation modelling, but rather, real-time statistical analyses based on mechanistic transmission models relying on available epidemiologic and virologic data. LESSONS LEARNT: A key lesson was that modelling cannot substitute for data; it can only make use of available data and highlight what additional data might best inform policy. Data gaps in 2009, especially from low-resource countries, made it difficult to evaluate severity, the effects of seasonal variation on transmission and the effectiveness of non-pharmaceutical interventions. Better communication between modellers and public health practitioners is needed to manage expectations, facilitate data sharing and interpretation and reduce inconsistency in results.
Keywords	Public aspects of medicine ; RA1-1270 ; Medicine ; R
Subject code	306
Language	English
Publishing date	2012-04-01T00:00:00Z
Publisher	World Health Organization
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Epidemic and intervention modelling

Maria D Van Kerkhove / Neil M Ferguson

Bulletin of the World Health Organization, Vol 90, Iss 4, Pp 306-

a scientific rationale for policy decisions? Lessons from the 2009 influenza pandemic

2012 Volume 310

Abstract	PROBLEM: Outbreak analysis and mathematical modelling are crucial for planning public health responses to infectious disease outbreaks, epidemics and pandemics. This paper describes the data analysis and mathematical modelling undertaken during and following the 2009 influenza pandemic, especially to inform public health planning and decision-making. APPROACH: Soon after A(H1N1)pdm09 emerged in North America in 2009, the World Health Organization convened an informal mathematical modelling network of public health and academic experts and modelling groups. This network and other modelling groups worked with policy-makers to characterize the dynamics and impact of the pandemic and assess the effectiveness of interventions in different settings. SETTING: The 2009 A(H1N1) influenza pandemic. RELEVANT CHANGES: Modellers provided a quantitative framework for analysing surveillance data and for understanding the dynamics of the epidemic and the impact of interventions. However, what most often informed policy decisions on a day-to-day basis was arguably not sophisticated simulation modelling, but rather, real-time statistical analyses based on mechanistic transmission models relying on available epidemiologic and virologic data. LESSONS LEARNT: A key lesson was that modelling cannot substitute for data; it can only make use of available data and highlight what additional data might best inform policy. Data gaps in 2009, especially from low-resource countries, made it difficult to evaluate severity, the effects of seasonal variation on transmission and the effectiveness of non-pharmaceutical interventions. Better communication between modellers and public health practitioners is needed to manage expectations, facilitate data sharing and interpretation and reduce inconsistency in results.
Keywords	Public aspects of medicine ; RA1-1270 ; Medicine ; R
Subject code	306
Language	English
Publishing date	2012-04-01T00:00:00Z
Publisher	World Health Organization
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Epidemic and intervention modelling

Maria D Van Kerkhove / Neil M Ferguson

Bulletin of the World Health Organization, Vol 90, Iss 4, Pp 306-

a scientific rationale for policy decisions? Lessons from the 2009 influenza pandemic

2012 Volume 310

Abstract	PROBLEM: Outbreak analysis and mathematical modelling are crucial for planning public health responses to infectious disease outbreaks, epidemics and pandemics. This paper describes the data analysis and mathematical modelling undertaken during and following the 2009 influenza pandemic, especially to inform public health planning and decision-making. APPROACH: Soon after A(H1N1)pdm09 emerged in North America in 2009, the World Health Organization convened an informal mathematical modelling network of public health and academic experts and modelling groups. This network and other modelling groups worked with policy-makers to characterize the dynamics and impact of the pandemic and assess the effectiveness of interventions in different settings. SETTING: The 2009 A(H1N1) influenza pandemic. RELEVANT CHANGES: Modellers provided a quantitative framework for analysing surveillance data and for understanding the dynamics of the epidemic and the impact of interventions. However, what most often informed policy decisions on a day-to-day basis was arguably not sophisticated simulation modelling, but rather, real-time statistical analyses based on mechanistic transmission models relying on available epidemiologic and virologic data. LESSONS LEARNT: A key lesson was that modelling cannot substitute for data; it can only make use of available data and highlight what additional data might best inform policy. Data gaps in 2009, especially from low-resource countries, made it difficult to evaluate severity, the effects of seasonal variation on transmission and the effectiveness of non-pharmaceutical interventions. Better communication between modellers and public health practitioners is needed to manage expectations, facilitate data sharing and interpretation and reduce inconsistency in results.
Keywords	Public aspects of medicine ; RA1-1270 ; Medicine ; R
Subject code	306
Language	English
Publishing date	2012-04-01T00:00:00Z
Publisher	World Health Organization
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Epidemic and intervention modelling

Maria D Van Kerkhove / Neil M Ferguson

Bulletin of the World Health Organization, Vol 90, Iss 4, Pp 306-

a scientific rationale for policy decisions? Lessons from the 2009 influenza pandemic

2012 Volume 310

Abstract	PROBLEM: Outbreak analysis and mathematical modelling are crucial for planning public health responses to infectious disease outbreaks, epidemics and pandemics. This paper describes the data analysis and mathematical modelling undertaken during and following the 2009 influenza pandemic, especially to inform public health planning and decision-making. APPROACH: Soon after A(H1N1)pdm09 emerged in North America in 2009, the World Health Organization convened an informal mathematical modelling network of public health and academic experts and modelling groups. This network and other modelling groups worked with policy-makers to characterize the dynamics and impact of the pandemic and assess the effectiveness of interventions in different settings. SETTING: The 2009 A(H1N1) influenza pandemic. RELEVANT CHANGES: Modellers provided a quantitative framework for analysing surveillance data and for understanding the dynamics of the epidemic and the impact of interventions. However, what most often informed policy decisions on a day-to-day basis was arguably not sophisticated simulation modelling, but rather, real-time statistical analyses based on mechanistic transmission models relying on available epidemiologic and virologic data. LESSONS LEARNT: A key lesson was that modelling cannot substitute for data; it can only make use of available data and highlight what additional data might best inform policy. Data gaps in 2009, especially from low-resource countries, made it difficult to evaluate severity, the effects of seasonal variation on transmission and the effectiveness of non-pharmaceutical interventions. Better communication between modellers and public health practitioners is needed to manage expectations, facilitate data sharing and interpretation and reduce inconsistency in results.
Keywords	Public aspects of medicine ; RA1-1270 ; Medicine ; R
Subject code	306
Language	English
Publishing date	2012-04-01T00:00:00Z
Publisher	World Health Organization
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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