Background An unprecedent increase in the number of cases and deaths reported from dengue virus (... more Background An unprecedent increase in the number of cases and deaths reported from dengue virus (DENV) infection has occurred in the southwestern Indian ocean in recent years. From 2017 to mid-2021 more than 70,000 confirmed dengue cases were reported in Reunion Island, and 1967 cases were recorded in the Seychelles from 2015 to 2016. Both these outbreaks displayed similar trends, with the initial circulation of DENV-2 which was replaced by DENV-1. Here, we aim to determine the origin of the DENV-1 epidemic strains and to explore their genetic characteristics along the uninterrupted circulation, particularly in Reunion. Methods Nucleic acids were extracted from blood samples collected from dengue positive patients; DENV-1 was identified by RT-qPCR. Positive samples were used to infect VERO cells. Genome sequences were obtained from either blood samples or infected-cell supernatants through a combination of both Illumina or MinION technologies. Results Phylogenetic analyses of partial or whole genome sequences revealed that all DENV-1 sequences from Reunion formed a monophyletic cluster that belonged to genotype I and were closely related to one isolate from Sri Lanka (OL752439.1, 2020). Sequences from the Seychelles belonged to the same major phylogenetic branch of genotype V, but fell into two paraphyletic clusters, with greatest similarity for one cluster to 2016-2017 isolate from Bangladesh, Singapore and China, and for the other cluster to ancestral isolates from Singapore, dating back to 2012. Compared to publicly available DENV-1 genotype I sequences, fifteen non-synonymous mutations were identified in the Reunion strains, including one in the capsid and the others in nonstructural proteins (NS) (three in NS1, two in NS2B, one in NS3, one in NS4B, and seven in NS5). Conclusion In contrast to what was seen in previous outbreaks, recent DENV-1 outbreaks in Reunion and the Seychelles were caused by distinct genotypes, all likely originating from Asia where dengue is (hyper)endemic in many countries. Epidemic DENV-1 strains from Reunion harbored specific non-synonymous mutations whose biological significance needs to be further investigated.
International Journal of Environmental Research and Public Health, Apr 6, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
reast and cervical cancer are considered significant healthcare issues for Canadian women, regard... more reast and cervical cancer are considered significant healthcare issues for Canadian women, regardless of race or ethnicity. Recent research continues to emphasize that they are a concern for women in all countries (Bur
<p>Pre-defined case definitions based on clinical and laboratory criteria, for each febrile... more <p>Pre-defined case definitions based on clinical and laboratory criteria, for each febrile illness included in the present analysis.</p
ABSTRACTElectronic clinical decision support algorithms (CDSAs) have been developed to address hi... more ABSTRACTElectronic clinical decision support algorithms (CDSAs) have been developed to address high childhood mortality and inappropriate antibiotic prescription by helping clinicians adhere to guidelines. Previously identified challenges of CDSAs include its limited scope, usability, and outdated clinical algorithms. To address these challenges we developed ePOCT+, a CDSA for the care of pediatric outpatients in low- and middle-income settings, and the medical algorithm suite (medAL-suite), a software for the creation and execution of CDSAs. Following the principles of digital development, we aim to describe the process and lessons learnt from the development of ePOCT+ and the medAL-suite.In particular, this work outlines the systematic integrative development process in the design and implementation of these tools required to meet the needs of clinicians to improve uptake and quality of care. We considered the feasibility, acceptability and reliability of clinical signs and sympto...
<p>Only results for which the LR+ was 2 and above or the LR- was 0.5 and below are provided... more <p>Only results for which the LR+ was 2 and above or the LR- was 0.5 and below are provided (otherwise the cell is left empty; if not applicable, NA is mentioned). LR with a 95% confidence interval (CI) that did not include 1 are in bold.</p
<p>Classification and regression trees analyses for single diseases. A. Malaria; B. Typhoid... more <p>Classification and regression trees analyses for single diseases. A. Malaria; B. Typhoid fever; C.Urinary tract infection; D. Radiological pneumonia; E.Human Herpes Virus 6 (HHV6) infection.</p
<p>Classification and regression trees analyses for groups of diseases. A. Bacterial diseas... more <p>Classification and regression trees analyses for groups of diseases. A. Bacterial disease; B. Viral disease.</p
Aim: To provide insight in the primary health care (PHC) case management of febrile children unde... more Aim: To provide insight in the primary health care (PHC) case management of febrile children under-five in Dar es Salaam, and to identify areas for improving quality of care.Methods: We used data from the routine care arm of the ePOCT trial, including children aged 2–59 months who presented with an acute febrile illness to two health centers in Dar es Salaam (2014–2016). The presenting complaint, anthropometrics, vital signs, test results, final diagnosis, and treatment were prospectively collected in all children. We used descriptive statistics to analyze the frequencies of diagnoses, adherence to diagnostics, and prescribed treatments.Results: We included 547 children (47% male, median age 14 months). Most diagnoses were viral: upper respiratory tract infection (60%) and/or gastro-enteritis (18%). Vital signs and anthropometric measurements taken by research staff and urinary testing failed to influence treatment decisions. In total, 518/547 (95%) children received antibiotics, wh...
Health of populations everywhere in the world has dramatically improved in the past years. Child ... more Health of populations everywhere in the world has dramatically improved in the past years. Child mortality halved in less than three decades. Life expectancy has increased in all countries and almost continuously since World War II, although large gaps still exist. However, one major threat for humanity remains for which we still don't have appropriate solutions: emerging infectious diseases (EID). We were collectively not very good in anticipating the last pandemic flu. We thought it would emerge from Southeast Asia, with an avian H5N1, when it came from Mexico, with a swine and avian strain of H1N1. We were not better in assessing the risk of Ebola in Western Africa, or Zika in Latin America and no one would dare to predict the evolution of the current outbreak in Democratic Republic of Congo (DRC). This special issue of JPHE focuses on a carefully selected set of EID and aims to learn from intelligent approaches to help better understanding the conditions that promote their emergence. Two groups of emerging viral pathogens are of primary concern here: (I) airborne viruses, and (II) arboviruses (arthropod-borne). The greatest threat of airborne viruses is due to the lack of measures to control airborne spread. Examples from the recent past highlight the pandemic potential of these viruses: the outbreaks of SARS-CoV in 2002/2003, the pandemic of influenza A/(H1N1)pdm09 in 2009 and the pandemic of MERS-CoV in 2012 with an unexpected international spread and a mortality rate of 40% (1). When a new respiratory pathogen emerges, immediate responses include increased surveillance, diagnostic assays to identify cases and ad-hoc mitigation strategies, like quarantining diseased persons. In the SARS-CoV outbreak, these measures eliminated the virus from the human population, but in the pandemic influenza A/(H1N1)pdm09, mitigation strategies had limited success and the virus quickly circulated around the globe. We are unlikely to ever been able to eradicate such viruses for which the human and animal reservoir is enormous. Therefore, continuing surveillance for local and imported cases and putative changes in virulence is essential. Dengue virus, the most widespread arbovirus, threatens 40% of the global population and infects 390 million people a year (2). Zika is now causing high morbidity through congenital infections and neurological disorders in the Americas. The European Centre for Disease Control (ECDC) reported the largest outbreak of West Nile Virus ever recorded in Europe in 2018 (3). Emerging arboviruses have similar ecological and evolutionary patterns, originating from a sylvatic origin, and adapting to urban nearby environments before spreading to humans around the globe (4). Vectors expansion must be closely monitored to track and ultimately prevent this emergence. Clinically, arboviruses are hard to diagnose since they present as an unspecific febrile illness, with many mild forms. Experts and leaders in global health and communities must join forces to detect, forecast, and contain these emerging outbreaks (5). We must do more than mitigate the impacts of outbreaks; we must get ahead of epidemics by combining traditional and innovative disease surveillance methods and leveraging new digital technologies, especially artificial intelligence (AI) (6). Today, AI systems are increasingly capable of complex reasoning on vast banks of medical data as well as on the complexity of human behaviors and real-world environments. In 2011, the IBM Watson system has won the well-known TV show of Jeopardy (7) which involves a not only encyclopaedic recall, but also the ability to reason about convoluted and often opaque statements and their relationship to the real world. Since then, the system has been continuously evolving and is gaining more and more acceptance as a decision support tool in medicine (8). It is well within the capacity of such systems to leverage their medical knowledge and elaborate world models to solve problems like linking occurrence of microcephaly by infected individuals with Zika. While the models which wrongly predicted a million cases of Ebola when actually less than 30,000 occurred, combining AI with modern simulation models can provide policy makers with a systematic, evidence-based assessment of the most probable effects of various measures. Such techniques allow us to consider complex multi-layered networks where each layer represents a particular strand of knowledge: core geography layer, epidemiological factors, biological factors, and social and economic factors. It is only through such multi-layered analysis and complex, that interweaved processes, such as disease spread, can be sustainably managed in today's complex world.
The 2016 Zika outbreak in the Americas was a public health emergency of international concern. Al... more The 2016 Zika outbreak in the Americas was a public health emergency of international concern. Alongside traditional approaches, several digital technologies were used to tackle this rapidly spreading global health threat. This work aimed to summarize the current state of research activity on the use of digital technologies during the Zika outbreak of 2015-2016 by providing an overview of the literature. A scoping review of publications indexed in the Web of Science and PubMed databases, published between 2016 and mid-2017 was conducted. Initial screening involved reviewing the title and abstract of identified literature before a full-text review was completed. Using a descriptive analytical method, we summarized the information presented in the studies. A total of 350 articles were screened with 57 found to describe the use of digital technologies with specific reference to the Zika outbreak. Several domains of digital technologies were identified including computational modelling (32/57), big data (including social media data) (19/57), mobile health (4/57), and other novel technologies (2/57), which were used for several purposes including disease monitoring (53/57), diagnostics (2/57) and treatment (2/57). Most articles (54/57) used a quantitative methodology. The majority of the studies (55/57) used non-experimental study designs with only two articles reporting experimental approaches. In terms of geographical focus, approximately half (27/57) of the published papers targeted the region of the Americas. This scoping review provided an overview of the current state of research on the utilization of digital technologies with specific reference to the Zika outbreak. The majority of articles reported the use of computational modelling and big data systems as core approaches, commonly dedicated to disease monitoring. Only a few studies described the use of mHealth and novel technologies. The findings indicate the potential value of digital technologies in the sphere of global health and outbreak response.
To construct evidence-based guidelines for management of febrile illness, it is essential to iden... more To construct evidence-based guidelines for management of febrile illness, it is essential to identify clinical predictors for the main causes of fever, either to diagnose the disease when no laboratory test is available or to better target testing when a test is available. The objective was to investigate clinical predictors of several diseases in a cohort of febrile children attending outpatient clinics in Tanzania, whose diagnoses have been established after extensive clinical and laboratory workup. From April to December 2008, 1005 consecutive children aged 2 months to 10 years with temperature ≥38°C attending two outpatient clinics in Dar es Salaam were included. Demographic characteristics, symptoms and signs, comorbidities, full blood count and liver enzyme level were investigated by bi- and multi-variate analyses (Chan, et al., 2008). To evaluate accuracy of combined predictors to construct algorithms, classification and regression tree (CART) analyses were also performed. 62...
The ongoing Ebola outbreak led to accelerated efforts to test vaccine candidates. On the basis of... more The ongoing Ebola outbreak led to accelerated efforts to test vaccine candidates. On the basis of a request by WHO, we aimed to assess the safety and immunogenicity of the monovalent, recombinant, chimpanzee adenovirus type-3 vector-based Ebola Zaire vaccine (ChAd3-EBO-Z). We did this randomised, double-blind, placebo-controlled, dose-finding, phase 1/2a trial at the Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland. Participants (aged 18-65 years) were randomly assigned (2:2:1), via two computer-generated randomisation lists for individuals potentially deployed in endemic areas and those not deployed, to receive a single intramuscular dose of high-dose vaccine (5 × 10(10) viral particles), low-dose vaccine (2·5 × 10(10) viral particles), or placebo. Deployed participants were allocated to only the vaccine groups. Group allocation was concealed from non-deployed participants, investigators, and outcome assessors. The safety evaluation was not masked for potentially dep...
Background An unprecedent increase in the number of cases and deaths reported from dengue virus (... more Background An unprecedent increase in the number of cases and deaths reported from dengue virus (DENV) infection has occurred in the southwestern Indian ocean in recent years. From 2017 to mid-2021 more than 70,000 confirmed dengue cases were reported in Reunion Island, and 1967 cases were recorded in the Seychelles from 2015 to 2016. Both these outbreaks displayed similar trends, with the initial circulation of DENV-2 which was replaced by DENV-1. Here, we aim to determine the origin of the DENV-1 epidemic strains and to explore their genetic characteristics along the uninterrupted circulation, particularly in Reunion. Methods Nucleic acids were extracted from blood samples collected from dengue positive patients; DENV-1 was identified by RT-qPCR. Positive samples were used to infect VERO cells. Genome sequences were obtained from either blood samples or infected-cell supernatants through a combination of both Illumina or MinION technologies. Results Phylogenetic analyses of partial or whole genome sequences revealed that all DENV-1 sequences from Reunion formed a monophyletic cluster that belonged to genotype I and were closely related to one isolate from Sri Lanka (OL752439.1, 2020). Sequences from the Seychelles belonged to the same major phylogenetic branch of genotype V, but fell into two paraphyletic clusters, with greatest similarity for one cluster to 2016-2017 isolate from Bangladesh, Singapore and China, and for the other cluster to ancestral isolates from Singapore, dating back to 2012. Compared to publicly available DENV-1 genotype I sequences, fifteen non-synonymous mutations were identified in the Reunion strains, including one in the capsid and the others in nonstructural proteins (NS) (three in NS1, two in NS2B, one in NS3, one in NS4B, and seven in NS5). Conclusion In contrast to what was seen in previous outbreaks, recent DENV-1 outbreaks in Reunion and the Seychelles were caused by distinct genotypes, all likely originating from Asia where dengue is (hyper)endemic in many countries. Epidemic DENV-1 strains from Reunion harbored specific non-synonymous mutations whose biological significance needs to be further investigated.
International Journal of Environmental Research and Public Health, Apr 6, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
reast and cervical cancer are considered significant healthcare issues for Canadian women, regard... more reast and cervical cancer are considered significant healthcare issues for Canadian women, regardless of race or ethnicity. Recent research continues to emphasize that they are a concern for women in all countries (Bur
<p>Pre-defined case definitions based on clinical and laboratory criteria, for each febrile... more <p>Pre-defined case definitions based on clinical and laboratory criteria, for each febrile illness included in the present analysis.</p
ABSTRACTElectronic clinical decision support algorithms (CDSAs) have been developed to address hi... more ABSTRACTElectronic clinical decision support algorithms (CDSAs) have been developed to address high childhood mortality and inappropriate antibiotic prescription by helping clinicians adhere to guidelines. Previously identified challenges of CDSAs include its limited scope, usability, and outdated clinical algorithms. To address these challenges we developed ePOCT+, a CDSA for the care of pediatric outpatients in low- and middle-income settings, and the medical algorithm suite (medAL-suite), a software for the creation and execution of CDSAs. Following the principles of digital development, we aim to describe the process and lessons learnt from the development of ePOCT+ and the medAL-suite.In particular, this work outlines the systematic integrative development process in the design and implementation of these tools required to meet the needs of clinicians to improve uptake and quality of care. We considered the feasibility, acceptability and reliability of clinical signs and sympto...
<p>Only results for which the LR+ was 2 and above or the LR- was 0.5 and below are provided... more <p>Only results for which the LR+ was 2 and above or the LR- was 0.5 and below are provided (otherwise the cell is left empty; if not applicable, NA is mentioned). LR with a 95% confidence interval (CI) that did not include 1 are in bold.</p
<p>Classification and regression trees analyses for single diseases. A. Malaria; B. Typhoid... more <p>Classification and regression trees analyses for single diseases. A. Malaria; B. Typhoid fever; C.Urinary tract infection; D. Radiological pneumonia; E.Human Herpes Virus 6 (HHV6) infection.</p
<p>Classification and regression trees analyses for groups of diseases. A. Bacterial diseas... more <p>Classification and regression trees analyses for groups of diseases. A. Bacterial disease; B. Viral disease.</p
Aim: To provide insight in the primary health care (PHC) case management of febrile children unde... more Aim: To provide insight in the primary health care (PHC) case management of febrile children under-five in Dar es Salaam, and to identify areas for improving quality of care.Methods: We used data from the routine care arm of the ePOCT trial, including children aged 2–59 months who presented with an acute febrile illness to two health centers in Dar es Salaam (2014–2016). The presenting complaint, anthropometrics, vital signs, test results, final diagnosis, and treatment were prospectively collected in all children. We used descriptive statistics to analyze the frequencies of diagnoses, adherence to diagnostics, and prescribed treatments.Results: We included 547 children (47% male, median age 14 months). Most diagnoses were viral: upper respiratory tract infection (60%) and/or gastro-enteritis (18%). Vital signs and anthropometric measurements taken by research staff and urinary testing failed to influence treatment decisions. In total, 518/547 (95%) children received antibiotics, wh...
Health of populations everywhere in the world has dramatically improved in the past years. Child ... more Health of populations everywhere in the world has dramatically improved in the past years. Child mortality halved in less than three decades. Life expectancy has increased in all countries and almost continuously since World War II, although large gaps still exist. However, one major threat for humanity remains for which we still don't have appropriate solutions: emerging infectious diseases (EID). We were collectively not very good in anticipating the last pandemic flu. We thought it would emerge from Southeast Asia, with an avian H5N1, when it came from Mexico, with a swine and avian strain of H1N1. We were not better in assessing the risk of Ebola in Western Africa, or Zika in Latin America and no one would dare to predict the evolution of the current outbreak in Democratic Republic of Congo (DRC). This special issue of JPHE focuses on a carefully selected set of EID and aims to learn from intelligent approaches to help better understanding the conditions that promote their emergence. Two groups of emerging viral pathogens are of primary concern here: (I) airborne viruses, and (II) arboviruses (arthropod-borne). The greatest threat of airborne viruses is due to the lack of measures to control airborne spread. Examples from the recent past highlight the pandemic potential of these viruses: the outbreaks of SARS-CoV in 2002/2003, the pandemic of influenza A/(H1N1)pdm09 in 2009 and the pandemic of MERS-CoV in 2012 with an unexpected international spread and a mortality rate of 40% (1). When a new respiratory pathogen emerges, immediate responses include increased surveillance, diagnostic assays to identify cases and ad-hoc mitigation strategies, like quarantining diseased persons. In the SARS-CoV outbreak, these measures eliminated the virus from the human population, but in the pandemic influenza A/(H1N1)pdm09, mitigation strategies had limited success and the virus quickly circulated around the globe. We are unlikely to ever been able to eradicate such viruses for which the human and animal reservoir is enormous. Therefore, continuing surveillance for local and imported cases and putative changes in virulence is essential. Dengue virus, the most widespread arbovirus, threatens 40% of the global population and infects 390 million people a year (2). Zika is now causing high morbidity through congenital infections and neurological disorders in the Americas. The European Centre for Disease Control (ECDC) reported the largest outbreak of West Nile Virus ever recorded in Europe in 2018 (3). Emerging arboviruses have similar ecological and evolutionary patterns, originating from a sylvatic origin, and adapting to urban nearby environments before spreading to humans around the globe (4). Vectors expansion must be closely monitored to track and ultimately prevent this emergence. Clinically, arboviruses are hard to diagnose since they present as an unspecific febrile illness, with many mild forms. Experts and leaders in global health and communities must join forces to detect, forecast, and contain these emerging outbreaks (5). We must do more than mitigate the impacts of outbreaks; we must get ahead of epidemics by combining traditional and innovative disease surveillance methods and leveraging new digital technologies, especially artificial intelligence (AI) (6). Today, AI systems are increasingly capable of complex reasoning on vast banks of medical data as well as on the complexity of human behaviors and real-world environments. In 2011, the IBM Watson system has won the well-known TV show of Jeopardy (7) which involves a not only encyclopaedic recall, but also the ability to reason about convoluted and often opaque statements and their relationship to the real world. Since then, the system has been continuously evolving and is gaining more and more acceptance as a decision support tool in medicine (8). It is well within the capacity of such systems to leverage their medical knowledge and elaborate world models to solve problems like linking occurrence of microcephaly by infected individuals with Zika. While the models which wrongly predicted a million cases of Ebola when actually less than 30,000 occurred, combining AI with modern simulation models can provide policy makers with a systematic, evidence-based assessment of the most probable effects of various measures. Such techniques allow us to consider complex multi-layered networks where each layer represents a particular strand of knowledge: core geography layer, epidemiological factors, biological factors, and social and economic factors. It is only through such multi-layered analysis and complex, that interweaved processes, such as disease spread, can be sustainably managed in today's complex world.
The 2016 Zika outbreak in the Americas was a public health emergency of international concern. Al... more The 2016 Zika outbreak in the Americas was a public health emergency of international concern. Alongside traditional approaches, several digital technologies were used to tackle this rapidly spreading global health threat. This work aimed to summarize the current state of research activity on the use of digital technologies during the Zika outbreak of 2015-2016 by providing an overview of the literature. A scoping review of publications indexed in the Web of Science and PubMed databases, published between 2016 and mid-2017 was conducted. Initial screening involved reviewing the title and abstract of identified literature before a full-text review was completed. Using a descriptive analytical method, we summarized the information presented in the studies. A total of 350 articles were screened with 57 found to describe the use of digital technologies with specific reference to the Zika outbreak. Several domains of digital technologies were identified including computational modelling (32/57), big data (including social media data) (19/57), mobile health (4/57), and other novel technologies (2/57), which were used for several purposes including disease monitoring (53/57), diagnostics (2/57) and treatment (2/57). Most articles (54/57) used a quantitative methodology. The majority of the studies (55/57) used non-experimental study designs with only two articles reporting experimental approaches. In terms of geographical focus, approximately half (27/57) of the published papers targeted the region of the Americas. This scoping review provided an overview of the current state of research on the utilization of digital technologies with specific reference to the Zika outbreak. The majority of articles reported the use of computational modelling and big data systems as core approaches, commonly dedicated to disease monitoring. Only a few studies described the use of mHealth and novel technologies. The findings indicate the potential value of digital technologies in the sphere of global health and outbreak response.
To construct evidence-based guidelines for management of febrile illness, it is essential to iden... more To construct evidence-based guidelines for management of febrile illness, it is essential to identify clinical predictors for the main causes of fever, either to diagnose the disease when no laboratory test is available or to better target testing when a test is available. The objective was to investigate clinical predictors of several diseases in a cohort of febrile children attending outpatient clinics in Tanzania, whose diagnoses have been established after extensive clinical and laboratory workup. From April to December 2008, 1005 consecutive children aged 2 months to 10 years with temperature ≥38°C attending two outpatient clinics in Dar es Salaam were included. Demographic characteristics, symptoms and signs, comorbidities, full blood count and liver enzyme level were investigated by bi- and multi-variate analyses (Chan, et al., 2008). To evaluate accuracy of combined predictors to construct algorithms, classification and regression tree (CART) analyses were also performed. 62...
The ongoing Ebola outbreak led to accelerated efforts to test vaccine candidates. On the basis of... more The ongoing Ebola outbreak led to accelerated efforts to test vaccine candidates. On the basis of a request by WHO, we aimed to assess the safety and immunogenicity of the monovalent, recombinant, chimpanzee adenovirus type-3 vector-based Ebola Zaire vaccine (ChAd3-EBO-Z). We did this randomised, double-blind, placebo-controlled, dose-finding, phase 1/2a trial at the Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland. Participants (aged 18-65 years) were randomly assigned (2:2:1), via two computer-generated randomisation lists for individuals potentially deployed in endemic areas and those not deployed, to receive a single intramuscular dose of high-dose vaccine (5 × 10(10) viral particles), low-dose vaccine (2·5 × 10(10) viral particles), or placebo. Deployed participants were allocated to only the vaccine groups. Group allocation was concealed from non-deployed participants, investigators, and outcome assessors. The safety evaluation was not masked for potentially dep...
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