1
|
Prem K, Cook AR, Jit M. Projecting social contact matrices in 152 countries using contact surveys and demographic data. PLoS Comput Biol 2017; 13:e1005697. [PMID: 28898249 PMCID: PMC5609774 DOI: 10.1371/journal.pcbi.1005697] [Citation(s) in RCA: 441] [Impact Index Per Article: 63.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Revised: 09/22/2017] [Accepted: 07/25/2017] [Indexed: 11/19/2022] Open
Abstract
Heterogeneities in contact networks have a major effect in determining whether a pathogen can become epidemic or persist at endemic levels. Epidemic models that determine which interventions can successfully prevent an outbreak need to account for social structure and mixing patterns. Contact patterns vary across age and locations (e.g. home, work, and school), and including them as predictors in transmission dynamic models of pathogens that spread socially will improve the models' realism. Data from population-based contact diaries in eight European countries from the POLYMOD study were projected to 144 other countries using a Bayesian hierarchical model that estimated the proclivity of age-and-location-specific contact patterns for the countries, using Markov chain Monte Carlo simulation. Household level data from the Demographic and Health Surveys for nine lower-income countries and socio-demographic factors from several on-line databases for 152 countries were used to quantify similarity of countries to estimate contact patterns in the home, work, school and other locations for countries for which no contact data are available, accounting for demographic structure, household structure where known, and a variety of metrics including workforce participation and school enrolment. Contacts are highly assortative with age across all countries considered, but pronounced regional differences in the age-specific contacts at home were noticeable, with more inter-generational contacts in Asian countries than in other settings. Moreover, there were variations in contact patterns by location, with work-place contacts being least assortative. These variations led to differences in the effect of social distancing measures in an age structured epidemic model. Contacts have an important role in transmission dynamic models that use contact rates to characterize the spread of contact-transmissible diseases. This study provides estimates of mixing patterns for societies for which contact data such as POLYMOD are not yet available.
Collapse
Affiliation(s)
- Kiesha Prem
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Alex R. Cook
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
| | - Mark Jit
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Modelling and Economics Unit, Health Protection Agency Centre for Infections, London, United Kingdom
| |
Collapse
|
2
|
Yang S, Zhou Y, Cui Y, Ding C, Wu J, Deng M, Wang C, Lu X, Chen X, Li Y, Shi D, Mi F, Li L. The need for strengthening the influenza virus detection ability of hospital clinical laboratories: an investigation of the 2009 pandemic. Sci Rep 2017; 7:43433. [PMID: 28281544 PMCID: PMC5345031 DOI: 10.1038/srep43433] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 01/24/2017] [Indexed: 01/25/2023] Open
Abstract
Most hospital clinical laboratories (HCLs) in China are unable to perform influenza virus detection. It remains unclear whether the influenza detection ability of HCLs influences the early identification and mortality rate of influenza. A total of 739 hospitalized patients with 2009 influenza A (H1N1) virus treated at 65 hospitals between May and December, 2009, in Zhejiang, China, were included based on identifications by HCLs and by public health laboratories (PHLs) of the Centers for Disease Control and Prevention. Of the patients, 407 (55.1%) were male, 17 died, resulting in an in-hospital mortality rate of 2.3%, and 297 patients were identified by HCLs and 442 by PHLs. The results indicated that a 24-hour delay in identification led to a 13% increase in the odds of death (OR = 1.13, P < 0.05). The time between onset and identification (3.9 days) of the HCL cohort was significantly shorter than that of the PHL cohort (4.8 days). The in-hospital mortality rate of the HCL group was significantly lower than that of the PHL group (1.0% vs. 3.2%, P < 0.05). HCL-based detection decreased the in-hospital mortality rate by 68.8%. HCL-based influenza virus detection facilitated early identification and reduced influenza mortality, and influenza detection ability of HCLs should be strengthened.
Collapse
Affiliation(s)
- Shigui Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Yuqing Zhou
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Yuanxia Cui
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Cheng Ding
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Jie Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Min Deng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Chencheng Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Xiaoqing Lu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Xiaoxiao Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Yiping Li
- Zhejiang Institute of Medical-care Information Technology, Hangzhou 311112, China
| | - Dongyan Shi
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Fenfang Mi
- Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| |
Collapse
|
3
|
Koh MT, Eg KP, Loh SS. Hospitalised Malaysian children with pandemic (H1N1) 2009 influenza: clinical characteristics, risk factors for severe disease and comparison with the 2002-2007 seasonal influenza. Singapore Med J 2015; 57:81-6. [PMID: 26768169 DOI: 10.11622/smedj.2015146] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
INTRODUCTION The pandemic caused by the H1N1 influenza virus in 2009 resulted in extensive morbidity and mortality worldwide. As the virus was a novel virus, there was limited data available on the clinical effects of the virus on children in Malaysia. Herein, we describe the clinical characteristics of children hospitalised with H1N1 influenza in a tertiary care centre; we also attempted to identify the risk factors associated with disease severity. METHODS In this retrospective study, we compared the characteristics of the children who were admitted into the University of Malaya Medical Centre, Malaysia, for H1N1 influenza during the pandemic with those who were admitted for seasonal influenza in 2002-2007. RESULTS Among the 77 children (aged ≤ 12 years) admitted to the centre due to H1N1 influenza from 1 July 2009-30 June 2010, nearly 60% were aged < 6 years and 40.3% had an underlying medical condition. The top three underlying medical conditions were bronchial asthma (14.3%), cardiac disease (10.4%) and neurological disorder (11.7%). The risk factors for severe disease were age < 2 years, underlying bronchial asthma and chronic lung disease. The three patients who died had a comorbid medical condition. The underlying cause of the deaths was acute respiratory distress syndrome or shock. CONCLUSION The clinical presentation of the children infected with the pandemic (H1N1) 2009 influenza virus did not differ significantly from that of children infected with seasonal influenza. However, there were more complaints of fever, cough and vomiting in the former group.
Collapse
Affiliation(s)
- Mia Tuang Koh
- Department of Paediatrics, University of Malaya, Kuala Lumpur, Malaysia
| | - Kah Peng Eg
- Department of Paediatrics, University of Malaya, Kuala Lumpur, Malaysia
| | - Soon Shan Loh
- Department of Medicine, Changi General Hospital, Singapore
| |
Collapse
|
4
|
Feng F, Xia G, Shi Y, Zhang Z. Longitudinal changes of pneumonia complicating novel influenza A (H1N1) by high-resolution computed tomography. RADIOLOGY OF INFECTIOUS DISEASES 2015; 2:40-46. [PMID: 32289066 PMCID: PMC7104186 DOI: 10.1016/j.jrid.2015.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Accepted: 02/27/2015] [Indexed: 11/25/2022]
Abstract
Purpose To assess lung lesions in patients with pneumonia complicating novel influenza A (H1N1) by serial high-resolution computed tomography (HRCT) during the early, progressive and convalescent stages. Samples and methods Serial HRCT scans in 39 patients with pneumonia complicating novel influenza A (H1N1) were reviewed for predominant patterns of lung abnormalities as well as distribution and extent of involvement. Longitudinal changes were assessed at different time points. Results In the early stage, the most common HRCT finding was patchy ground-glass opacity (GGO) (n = 4, 54.7%). In the progressive stage, bilaterally distributed GGO mixed with consolidation was the most commonly observed feature (n = 28, 71.8%). The diffuse pattern deteriorated to a peak (n = 17, 43.6%) at this stage. In the convalescent stage, the most common finding was fibrosis (n = 25, 64.1%). Averagely, fibrosis was observed at d 18.5 ± 6.4 after the onset of symptoms. Three patterns of longitudinal changes of the lesions were observed, including: type 1, improvement after deterioration; type 2, concurrent improvement and deterioration followed by improvement; and type 3, gradual improvement. Type 1 was the more common pattern (n = 27, 69.2%). Complete serial HRCT scans from initial and final scan were obtained in 24 patients, and the mean CT score peaked at d 8–14 of the illness. Conclusion HRCT may play a role in detecting and characterizing pulmonary lesions for the cases of pneumonia complicating influenza A. In addition, it may contribute to monitoring longitudinal changes of pneumonia and assessing therapeutic response.
Collapse
|
5
|
Epidemiological and virological characteristics of pandemic influenza A (H1N1) school outbreaks in China in 2009. PLoS One 2012; 7:e45898. [PMID: 23029300 PMCID: PMC3459944 DOI: 10.1371/journal.pone.0045898] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2011] [Accepted: 08/23/2012] [Indexed: 11/19/2022] Open
Abstract
Background During the 2009 pandemic influenza H1N1 (2009) virus (pH1N1) outbreak, school students were at an increased risk of infection by the pH1N1 virus. However, the estimation of the attack rate showed significant variability. Methods Two school outbreaks were investigated in this study. A questionnaire was designed to collect information by interview. Throat samples were collected from all the subjects in this study 6 times and sero samples 3 times to confirm the infection and to determine viral shedding. Data analysis was performed using the software STATA 9.0. Findings The attack rate of the pH1N1 outbreak was 58.3% for the primary school, and 52.9% for the middle school. The asymptomatic infection rates of the two schools were 35.8% and 37.6% respectively. Peak virus shedding occurred on the day of ARI symptoms onset, followed by a steady decrease over subsequent days (p = 0.026). No difference was found either in viral shedding or HI titer between the symptomatic and the asymptomatic infectious groups. Conclusions School children were found to be at a high risk of infection by the novel virus. This may be because of a heightened risk of transmission owing to increased mixing at boarding school, or a lack of immunity owing to socio-economic status. We conclude that asymptomatically infectious cases may play an important role in transmission of the pH1N1 virus.
Collapse
|
6
|
Low influenza vaccination rates among child care workers in the United States: assessing knowledge, attitudes, and behaviors. J Community Health 2012; 37:272-81. [PMID: 21938550 DOI: 10.1007/s10900-011-9478-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
Influenza can spread quickly among children and caregivers in child day care settings. Vaccination is the most effective method to prevent influenza. We determined 2009 pandemic influenza A (H1N1) (pH1N1) and seasonal influenza vaccination rates during the 2009-2010 influenza season among child care center employees, assessed knowledge and attitudes regarding the vaccines, and determined factors associated with vaccine receipt. Using a cross-sectional study design, from January 30-March 1, 2010, we surveyed 384 (95%) of 403 employees at 32 licensed child centers in the United States about personal and work characteristics, vaccine receipt, and knowledge and attitudes regarding each vaccine. Forty-five (11%) and eighty five (22%) respondents reported receiving the pH1N1 and seasonal influenza vaccines, respectively. The most common reasons cited for not getting either vaccine were "I don't think I need the vaccine," "I don't think the vaccine will keep me from getting the flu," and "the vaccine is not safe." Factors independently associated with receipt of either vaccine included belief in its efficacy, having positive attitudes towards it, and feeling external pressure to get it. Child care center employees had low rates of pH1N1 and seasonal influenza vaccination largely due to misconceptions about the need for and efficacy of the vaccine. Public health messages should address misconceptions about vaccines, and employers should consider methods to maximize influenza vaccination of employees as part of a comprehensive influenza prevention program.
Collapse
|
7
|
Fabbiani M, Sali M, Di Cristo V, Pignataro G, Prete V, Farina S, D'Avino A, Manzara S, Dal Verme LZ, Silveri NG, Cauda R, Delogu G, Fadda G, Di Giambenedetto S. Prospective evaluation of epidemiological, clinical, and microbiological features of pandemic influenza A (H1N1) virus infection in Italy. J Med Virol 2012; 83:2057-65. [PMID: 22012711 DOI: 10.1002/jmv.22231] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Since several characteristics of pandemic influenza A (H1N1) virus infection remain to be determined, this study aimed to describe clinical features and complications of patients infected with H1N1. Subjects affected by influenza-like illnesses and a control group of asymptomatic patients were enrolled prospectively at an Emergency Department from October 2009 to April 2010. At enrollment, clinical data and nasopharyngeal swabs for virological analyses were obtained. Ill subjects were followed until recovery and swabs were collected weekly in patients infected with H1N1. Of 318 patients enrolled, 92 (28.9%) were positive to H1N1. Patients infected with H1N1 were mainly young adults and complained classic influenza-like symptoms. Fever was observed for a median time of 5 (IQR 3-7) days. Hospitalization occurred in 27.7% with 2% requiring intensive care unit admission: median length of hospitalization was 6 days (IQR 5-9). Pneumonia was diagnosed in 19.6% of patients. A similar proportion of lower airways involvement and of clinical complications was observed in subjects testing positive or negative for H1N1. However, patients infected with H1N1 were younger and hospitalized for a shorter period as compared to the control group (P = 0.002 and P = 0.045, respectively). Older age, asthma/chronic obstructive pulmonary disease and hypertension were associated with an increased risk of pneumonia. Viral shedding was observed for at least 1 week in 21.3% of patients. Asymptomatic infection was uncommon (1.1%). Respiratory syndromes caused by H1N1 and factors associated with disease severity were investigated and compared to influenza-like illnesses of other origin. Such findings might contribute to improve clinical and epidemiological management of the disease.
Collapse
Affiliation(s)
- Massimiliano Fabbiani
- Institute of Clinical Infectious Diseases, Catholic University of Sacred Heart, Rome, Italy.
| | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
8
|
Kwon NH, Kim JE, Cho BK, Park HJ. A novel influenza a (H1N1) virus as a possible cause of pityriasis rosea? J Eur Acad Dermatol Venereol 2011; 25:368-9. [PMID: 20561127 DOI: 10.1111/j.1468-3083.2010.03725.x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
|
9
|
Cox CM, Blanton L, Dhara R, Brammer L, Finelli L. 2009 Pandemic influenza A (H1N1) deaths among children--United States, 2009-2010. Clin Infect Dis 2011; 52 Suppl 1:S69-74. [PMID: 21342902 DOI: 10.1093/cid/ciq011] [Citation(s) in RCA: 97] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The 2009 pandemic influenza A (H1N1) (pH1N1) virus emerged in the United States in April 2009 (1) and has since caused significant morbidity and mortality worldwide (2-6). We compared pandemic influenza A (H1N1) (pH1N1)-associated deaths occurring from 15 April 2009 through 23 January 2010 with seasonal influenza-associated deaths occurring from 1 October 2007 through 14 April 2009, a period during which data collected were most comparable. Among 317 children who died of pH1N1-associated illness, 301 (95%) had a reported medical history. Of those 301, 205 (68%) had a medical condition associated with an increased risk of severe illness from influenza. Children who died of pH1N1-associated illness had a higher median age (9.4 vs 6.2 years; P<.01) and longer time from onset of symptoms to death (7 vs 5 days, P<.01) compared with children who died of seasonal influenza-associated illness. The majority of pediatric deaths from pH1N1 were in older children with high-risk medical conditions. Vaccination continues to be critical for all children, especially those at increased risk of influenza-related complications.
Collapse
Affiliation(s)
- Chad M Cox
- Epidemic Intelligence Service, Office of Workforce and Career Development assigned to Influenza Division, Centers for DiseaseControl and Prevention, Atlanta, Georgia, USA.
| | | | | | | | | |
Collapse
|
10
|
Giambenedetto S, Zileri Dal Verme L, Sali M, Farina S, Cristo V, Manzara S, Luca A, Pignataro G, Prosperi M, Franco A, Gentiloni Silveri N, Delogu G, Cauda R, Fabbiani M, Fadda G. Clinical presentation, microbiological features and correlates of disease severity of 2009 pandemic influenza A (H1N1) infection. Eur J Clin Microbiol Infect Dis 2010; 30:541-9. [DOI: 10.1007/s10096-010-1116-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2010] [Accepted: 10/30/2010] [Indexed: 10/18/2022]
|