15 July 2015

Research Committee Selected Articles of the Week, July 13, 2015

Articles from July_06_2015

Research Committee Selected Articles for the Week of July_06_2015

  • Jiang L., Lee V.J., Lim W.Y., Chen M.I., Chen Y., Tan L., Lin R.T., Leo Y.S., Barr I., Cook A.R. Performance of case definitions for influenza surveillance
  • Hlavinkova L., Kristufkova Z., Mikas J. Risk factors for severe outcome of cases with pandemic influenza A(H1N1)pdm09
  • Barde P.V., Shukla M.K., Kori B.K., Chand G., Jain L., Varun B.M., Dutta D., Baruah K., Singh N. Emergence of dengue in tribal villages of Mandla district, Madhya Pradesh, India
  • Davila-Torres J., Chowell G., Borja-Aburto V.H., Viboud C., Grajalez-Muniz C., Miller M.A. Intense seasonal A/H1N1 influenza in Mexico, winter 2013-2014
  • Boggild A.K., Esposito D.H., Kozarsky P.E., Ansdell V., Beeching N.J., Campion D., Castelli F., Caum Differential diagnosis of illness in travelers arriving from sierra Leone, Liberia, or guinea: A cross-sectional study from the Geosentinel surveillance network
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    The movement pattern of horses around race meetings in New Zealand

    In order to describe the implications of racehorse movement on the potential spread and control of infectious disease in New Zealand, the movement of horses due to regular racing activities needed to be quantified. Race meeting, trainer and starter data we re collected in 2009 from the governing bodies for the two racing codes in New Zealand; Harness Racing New Zealand and New Zealand Thoroughbred Racing. During 2009, 507 Thoroughbred and 506 Standardbred race meetings were held. A random selection of 42 Sta ndardbred and 39 Thoroughbred race meetings were taken from all race meetings held in 2009 and the distances travelled by trainers to these race meetings were determined. The trainers attending selected race meetings represented 50% (1135/2287) of all regi stered trainers in 2009. There was no seasonal pattern of when race meetings were held between racing codes (P ? 0.18) or by race type (P ? 0.83). There were significant differences in the distance travelled by trainers to race meetings, by racing code (P < 0.001). Thoroughbred trainers travelled a median of 91 km (IQR 40-203 km), while Standardbred trainers travelled a median of 45 km (IQR 24-113 km) (P < 0.001). Within each racing code, trainers travelled further to attend premier races than other types o f race meetings (P < 0.001). These data demonstrate there is higher potential for more widespread disease dissemination from premier race meetings compared with other types of race meetings. Additionally, lack of a seasonal pattern indicates that a widespr ead outbreak could occur at any time of the year. Widespread disease dissemination would increase the logistic effort required for effective infectious disease control and has the potential to increase the time required to achieve control. © CSIRO 2015.

    Influenza-like illness (ILI) case definitions, such as those from the European Centre for Disease Control and Prevention, World Health Organization (WHO) and United States Centers for Disease Control and Prevention, are commonly used for influenza surveill ance. We assessed how various case definitions performed during the initial wave of influenza A(H1N1 pdm09 infections in Singapore on a cohort of 727 patients with two to three blood samples and whose symptoms were reviewed fortnightly from June to October 2009. Using seroconversion (? 4-fold rise) to A/California/7/2009 (H1N1), we identified 36 presumptive influenza A(H1N1)pdm09 episodes and 664 episodes unrelated to influenza A(H1N1)pdm09. Cough, fever and headache occurred more commonly in presumptive in fluenza A(H1N1)pdm09. Although the sensitivity was low (36%), the recently revised WHO ILI case definition gave a higher positive predictive value (42%) and positive likelihood ratio (13.3) than the other case definitions. Results including only episodes w ith primary care consultations were similar. Individuals who worked or had episodes with fever, cough or sore throat were more likely to consult a physician, while episodes with Saturday onset were less likely, with some consultations skipped or postponed. Our analysis supports the use of the revised WHO ILI case definition,which includes only cough in the presence of fever defined as body temperature ?38 °C for influenza surveillance. © 2015 European Centre for Disease Prevention and Control (ECDC). All ri ghts reserved.

    OBJECTIVES: The aim of this study is to describe demographic, clinical and epidemiological characteristics of cases with laboratory-confirmed pandemic influenza virus A(H1N1)pdm09 reported in Slovakia from May 28, 2009 to December 30, 2009 and analyse the association between risk factors and severe outcome of these cases. BACKGROUND: In the spring of 2009, an outbreak of a pandemic influenza virus A(H1N1)pdm09, emerged in Mexico and spread globally. Until December 2009, 1,014 cases were notified in Slovakia . METHODS: The data were collected within national influenza surveillance system. Odds ratios (95% CI) were calculated. Associations were found to be significantly associated with the worse outcome (p < 0.05) in the univariate analysis and were adjusted fo r possible effects of age and sex by using a logistic regression model. RESULTS: Out of the total number of 1,014 cases, 131 (12.9 %) cases were hospitalized, and 43 (4.2 %) of those were admitted to intensive care units. During the reporting period, 38 de aths were reported, representing a case fatality rate of 3.75 %. The median age of severe cases (35 years, IQR = 29 y) was significantly higher than the median age of mild cases (24 years, IQR = 19 y; p < 0.001). By using a logistic regression, we found ou t that chronic obstructive pulmonary disease (COPD) (aOR = 9.2; 95%CI: 1.42-59.98), cardiovascular diseases (aOR = 14.97; 95%CI: 5.49-40.79), malignity (aOR = 7.6; 95%CI: 1.95-29.37) and gravidity (aOR = 55.21; 95% CI: 14.40-211.58) were significantly asso ciated with severe outcomes of the cases. CONCLUSION: The fact, that 35% of severely ill patients did not report any risk factor suggests the importance of vaccination as a prevention of influenza.

    Background & objectives: Dengue (DEN) is a rapidly spreading arboviral disease transmitted by Aedes mosquitoes. Although it is endemic in India, dengue virus (DENV) infection has not been reported from tribal areas of Madhya Pradesh. Investigations were co nducted to establish the aetiology of sudden upsurge of cases with febrile illness in June 2013 from tribal villages of Mandla district of Madhya Pradesh, India. Methods: The rapid response team of the National Institute for Research in Tribal Health, Jaba lpur, conducted clinical investigations and field surveys to collect the samples from suspected cases. Samples were tested using molecular and serological tools. Collected mosquitoes were identified and tested for the presence of virus using semi nested re verse transcriptase-polymerase chain reaction (nRT-PCR). The sequences were analysed to identify serotype and genotype of the virus. Results: of the 648 samples collected from 18 villages of Mandla, 321 (49.53%) were found to be positive for dengue. The nR T-PCR and sequencing confirmed the aetiology as dengue virus type 2. Eighteen per cent of patients needed hospitalization and five deaths were attributed to dengue. The virus was also detected from Aedes aegypti mosquito, which was incriminated as a vector . Phylogenetic analysis revealed that the dengue virus 2 detected belonged to cosmopolitan genotype of the virus. Interpretation & conclusions: Dengue virus serotype 2 was detected as the aetiological agent in the outbreak in tribal villages of Mandla dist rict of Madhya Pradesh. Conducive man-made environment favouring mosquitogenic conditions and seeding of virus could be the probable reasons for this outbreak. Urgent attention is needed to control this new threat to tribal population, which is already ove rburdened with other vector borne diseases. © 2015, Indian Council of Medical Research. All rights reserved.

    Background and Aims: A recrudescent wave of pandemic influenza A/H1N1 affected Mexico during the winter of 2013-2014 following a mild 2012-2013 A/H3N2 influenza season. Methods: We compared the demographic and geographic characteristics of hospitalizations and inpatient deaths for severe acute respiratory infection (SARI) and laboratory-confirmed influenza during the 2013-2014 influenza season compared to previous influenza seasons, based on a large prospective surveillance system maintained by the Mexican Social Security health care system. Results: A total of 14,236 SARI hospitalizations and 1,163 inpatient deaths (8.2%) were reported between October 1, 2013 and March 31, 2014. Rates of laboratory-confirmed A/H1N1 hospitalizations and deaths were significa ntly higher among individuals aged 30-59years and lower among younger age groups for the 2013-2014 A/H1N1 season compared to the previous A/H1N1 season in 2011-2012 (?2 test, p<0 data-blogger-escaped-.001="" data-blogger-escaped-1.3-1.4="" data-blogger-escaped-2011-2012="" data-blogger-escaped-2013-2014="" data-blogger-escaped-2013-march="" data-blogger-escaped-2014="" data-blogger-escaped-2015="" data-blogger-escaped-a="" data-blogger-escaped-absence="" data-blogger-escaped-activity="" data-blogger-escaped-adults="" data-blogger-escaped-age="" data-blogger-escaped-among="" data-blogger-escaped-and="" data-blogger-escaped-antigenic="" data-blogger-escaped-at="" data-blogger-escaped-build-up="" data-blogger-escaped-but="" data-blogger-escaped-c="" data-blogger-escaped-ce="" data-blogger-escaped-change="" data-blogger-escaped-clear="" data-blogger-escaped-conclusions:="" data-blogger-escaped-deaths="" data-blogger-escaped-disease="" data-blogger-escaped-distribution="" data-blogger-escaped-documented="" data-blogger-escaped-drift="" data-blogger-escaped-during="" data-blogger-escaped-estimated="" data-blogger-escaped-for="" data-blogger-escaped-from="" data-blogger-escaped-globally="" data-blogger-escaped-gradual="" data-blogger-escaped-hospitalizations="" data-blogger-escaped-immunity="" data-blogger-escaped-imss.="" data-blogger-escaped-in2009.="" data-blogger-escaped-in="" data-blogger-escaped-increase="" data-blogger-escaped-infections="" data-blogger-escaped-influenza="" data-blogger-escaped-initial="" data-blogger-escaped-irculating="" data-blogger-escaped-line="" data-blogger-escaped-lower="" data-blogger-escaped-mexico="" data-blogger-escaped-middle-aged="" data-blogger-escaped-ntral="" data-blogger-escaped-number="" data-blogger-escaped-observed="" data-blogger-escaped-october="" data-blogger-escaped-of="" data-blogger-escaped-pandemic="" data-blogger-escaped-pandemics.="" data-blogger-escaped-past="" data-blogger-escaped-period="" data-blogger-escaped-populations="" data-blogger-escaped-post-2009="" data-blogger-escaped-preceding="" data-blogger-escaped-profile="" data-blogger-escaped-proportionate="" data-blogger-escaped-related="" data-blogger-escaped-relative="" data-blogger-escaped-reminiscent="" data-blogger-escaped-reported="" data-blogger-escaped-reproduction="" data-blogger-escaped-season.="" data-blogger-escaped-season="" data-blogger-escaped-severe="" data-blogger-escaped-shift="" data-blogger-escaped-slow="" data-blogger-escaped-substantial="" data-blogger-escaped-suggests="" data-blogger-escaped-than="" data-blogger-escaped-that="" data-blogger-escaped-the="" data-blogger-escaped-to="" data-blogger-escaped-viruses="" data-blogger-escaped-was="" data-blogger-escaped-waves="" data-blogger-escaped-we="" data-blogger-escaped-winter="" data-blogger-escaped-with="" data-blogger-escaped-younger="">

    Background: The largest-ever outbreak of Ebola virus disease (EVD), ongoing in West Africa since late 2013, has led to export of cases to Europe and North America. Clinicians encountering ill travelers arriving from countries with widespread Ebola virus tr ansmission must be aware of alternate diagnoses associated with fever and other nonspecific symptoms. Objective: To define the spectrum of illness observed in persons returning from areas of West Africa where EVD transmission has been widespread. Design: D escriptive, using GeoSentinel records. Setting: 57 travel or tropical medicine clinics in 25 countries. Patients: 805 ill returned travelers and new immigrants from Sierra Leone, Liberia, or Guinea seen between September 2009 and August 2014. Measurements: Frequencies of demographic and travelrelated characteristics and illnesses reported. Results: The most common specific diagnosis among 770 nonimmigrant travelers was malaria (n = 310 [40.3%]), with Plasmodium falciparum or severe malaria in 267 (86%) and non-P. falciparum malaria in 43 (14%). Acute diarrhea was the second most common diagnosis among nonimmigrant travelers (n= 95 [12.3%]). Such common diagnoses as upper respiratory tract infection, urinary tract infection, and influenza-like illness occurre d in only 26, 9, and 7 returning travelers, respectively. Few instances of typhoid fever (n = 8), acute HIV infection (n = 5), and dengue (n = 2) were encountered.
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