Complete sequence and phylogenetic characterisation of Crimean–Congo hemorrhagic fever virus from Afghanistan

Ölschläger, Stephan; Gabriel, Marcin; Schmidt‐Chanasit, Jonas; Meyer, Martin; Osborn, Erik; Conger, Nickolas G.; Allan, Patrick F.; Günther, Stephan

doi:10.1016/j.jcv.2010.09.018

Cited by 36 publications

(28 citation statements)

References 5 publications

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“…Since the health system is not able to intervene in weather variability, ceasing LIP in spring and summer, or more suitable quarantine in the border areas, could help to prevent outbreaks. It should be noted that, in accord with the results of previous studies, the CCHFV genome isolated from Iranian patients is similar to that from Afghanistan and Pakistan that hasa close relationship with the CCHF Matin strain [2,3,12,32,33]; therefore the migration of CCHFV is free and unrestricted between Iran and Pakistan [34].…”

Section: Discussionsupporting

confidence: 85%

Predicting CCHF incidence and its related factors using time-series analysis in the southeast of Iran: comparison of SARIMA and Markov switching models

et al. 2014

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Crimean-Congo haemorrhagic fever (CCHF) is endemic in the southeast of Iran. This study aimed to predict the incidence of CCHF and its related factors and explore the possibility of developing an empirical forecast system using time-series analysis of 13 years' data. Data from 2000 to 2012 were obtained from the Health Centre of Zahedan University of Medical Sciences, Climate Organization and the Veterinary Organization in the southeast of Iran. Seasonal autoregressive integrated moving average (SARIMA) and Markov switching models (MSM) were performed to examine the potential related factors of CCHF outbreaks. These models showed that the mean temperature (°C), accumulated rainfall (mm), maximum relative humidity (%) and legal livestock importation from Pakistan (LIP) were significantly correlated with monthly incidence of CCHF in different lags (P < 0·05). The modelling fitness was checked with data from 2013. Model assessments indicated that the MSM had better predictive ability than the SARIMA model [MSM: root mean square error (RMSE) 0·625, Akaike's Information Criterion (AIC) 266·33; SARIMA: RMSE 0·725, AIC 278·8]. This study shows the potential of climate indicators and LIP as predictive factors in modelling the occurrence of CCHF. Our results suggest that MSM provides more information on outbreak detection and can be a better predictive model compared to a SARIMA model for evaluation of the relationship between explanatory variables and the incidence of CCHF.

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Section: Discussionsupporting

confidence: 85%

Predicting CCHF incidence and its related factors using time-series analysis in the southeast of Iran: comparison of SARIMA and Markov switching models

et al. 2014

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“…Transmission of infected mature and immature ticks by rodents and birds and also by skin and hide trades from Sistan-Balochistan province of Iran to Pakistan may be the reason for the second surge in Baluchistan province of Pakistan. It must be mentioned that as in the results of previous studies, infestation with Hyalomma among wild rodents is more common than with other tick species in southeast Iran [8] and that the CCHFV genome isolated from Iranian patients is similar to Afghanistan and Pakistan, which have a close relationship with the CCHF Matin strain [7,11,13,25,26].…”

Section: Discussionmentioning

confidence: 88%

Crimean-Congo hemorrhagic fever and its relationship with climate factors in southeast Iran: a 13-year experience

Ansari

Shafiei

Izadi

et al. 2014

J Infect Dev Ctries

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Introduction: Crimean-Congo hemorrhagic fever (CCHF) is endemic in southeast Iran. In this study we present the epidemiological features of CCHF and its relationship with climate factors in over a 13-year span. Methodology: Surveillance system data of CCHF from 2000 to 2012 were obtained from the Province Health Centre of Zahedan University of Medical Sciences in southeast Iran. The climate data were obtained from the climate organization. The seasonal auto-regression integrated moving average (SARIMA) model was used for time series analysis to produce a model as applicable as possible in predicting the variations in the occurrence of the disease. Results: Between 2000 and 2012, 647 confirmed CCHF cases were reported from Sistan-va-Baluchistan province. The total case fatality rate was about 10.0%. Climate variables including mean temperature (°C), accumulated rainfall (mm), and maximum relative humidity (%) were significantly correlated with monthly incidence of CCHF (p <0.05). There was no clear pattern of decline in the reported number of cases within the study's time span. The first spike in the number of CCHF cases in Iran occurred after the first surge of the disease in Pakistan. Conclusions: This study shows the potential of climate indicators as predictive factors in modeling the occurrence of CCHF, even though it has to be appreciated whether there is any need for a practically applicable model. There are also other factors, such as entomological indicators and virological finding that must be considered.

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“…However, complete S, M and L sequences are available for only four isolates collected from humans and one tick isolate from South Africa. These, as well as other published CCHFV sequences, were determined by Sanger sequencing using primer walking [6][7][8][9][10][11][12][13][14][15][16][17][18]. In recent years, a number of nextgeneration sequencing (NGS) methods have been developed which yield large amounts of sequencing data at relatively low cost.…”

Section: Introductionmentioning

confidence: 99%

Next-generation sequencing of southern African Crimean-Congo haemorrhagic fever virus isolates reveals a high frequency of M segment reassortment

et al. 2014

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SUMMARYCrimean Congo haemorrhagic fever virus (CCHFV) is a bunyavirus with a single-stranded RNA genome consisting of three segments (S, M, L), coding for the nucleocapsid protein, envelope glycoproteins and RNA polymerase, respectively. To date only five complete genome sequences are available from southern African isolates. Complete genome sequences were generated for 10 southern African CCHFV isolates using next-generation sequencing techniques. The maximum-likelihood method was used to generate tree topologies for 15 southern African plus 26 geographically distinct complete sequences from GenBank. M segment reassortment was identified in 10/15 southern African isolates by incongruencies in grouping compared to the S and L segments. These reassortant M segments cluster with isolates from Asia/Middle East, while the S and L segments cluster with strains from South/West Africa. The CCHFV M segment shows a high level of genetic diversity, while the S and L segments appear to co-evolve. The reason for the high frequency of M segment reassortment is not known. It has previously been suggested that M segment reassortment results in a virus with high fitness but a clear role in increased pathogenicity has yet to be shown.

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Complete sequence and phylogenetic characterisation of Crimean–Congo hemorrhagic fever virus from Afghanistan

Cited by 36 publications

References 5 publications

Predicting CCHF incidence and its related factors using time-series analysis in the southeast of Iran: comparison of SARIMA and Markov switching models

Predicting CCHF incidence and its related factors using time-series analysis in the southeast of Iran: comparison of SARIMA and Markov switching models

Crimean-Congo hemorrhagic fever and its relationship with climate factors in southeast Iran: a 13-year experience

Next-generation sequencing of southern African Crimean-Congo haemorrhagic fever virus isolates reveals a high frequency of M segment reassortment

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