Crimean-Congo haemorrhagic fever (CCHF) is an emerging zoonotic disease in India which is prevalent in neighbouring countries. CCHF virus (CCHFV) is a widespread tick-borne virus which is endemic in Africa, Asia, Eastern Europe and the Middle East. In the present study, samples of clinically suspected human cases from different areas of northern-western India were tested for the presence of CCHFV by RT–PCR through amplification of nucleocapsid (N) gene of CCHFV. Positive samples were sequenced to reveal the prevailing CCHFV genotype(s) and phylogenetic relatedness. A phylogenetic tree revealed the emergence of diverse strains in the study region showing maximum identity with the Pakistan, Afghanistan and Iran strains, which was different from earlier reported Indian strains. Our findings reveal for the first time the emergence of the Asia 1 group in India; while earlier reported CCHFV strains belong to the Asia 2 group.

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.

Crimean-Congo haemorrhagic fever (CCHF) is endemic in Turkey, and since 2004 many cases have been reported from different regions of Turkey. There are limited data about the seroprevalence of the disease in household members of patients or persons sharing the same environment. We evaluated seroprevalence of CCHF in the immediate neighbourhood and in household members of patients living in the same environment as confirmed cases of CCHF in an endemic area of Turkey. A total of 625 healthy subjects [mean (s.d.) age: 42·3 (18·4) years, 58·7% females] without a past history of CCHF infection included in this case-control, retrospective study were evaluated in terms of sociodemographic characteristics, risk factors for CCHF via a study questionnaire, while serum analysis for CCHF virus (CCHFV) IgG antibodies was performed by ELISA. Anti-CCHFV IgG antibodies were positive in 85 (13·6%) participants. None of the seropositive individuals had a history of symptomatic infection. Regression analysis revealed that animal husbandry [odds ratio (OR) 1·84, 95% confidence interval (CI) 1·09–3·11], contact with animals (OR 2·31, 95% CI 1·08–5·10), contact with ticks (OR 3·45, 95% CI 1·87–6·46), removing ticks from animals by hand (OR 2·48, 95% CI 1·48–4·18) and living in a rural area (OR 4·05, 95% CI 1·65–10·56) were associated with increased odds of having IgG seropositivity, while being a household member of a patient with prior CCHF infection had no influence on seropositivity rates. This result also supports the idea that CCHF is not transmitted person-to-person by the airborne route.

We report a nosocomial outbreak of Crimean-Congo haemorrhagic fever (CCHF) that affected six patients in June 2009 in Ghaem Hospital, Mashhad, Iran, apparently related to one index case. The last four cases were healthcare workers. Infection was spread by percutaneous exposure to two cases, and probably by direct contact with blood, clothes and sheets, to three others. The diagnosis in the two fatal cases was not confirmed virologically. The diagnosis in four cases who survived was confirmed by specific reverse transcription polymerase chain reaction. The patients were treated with ribavirin. In endemic areas, every patient presenting with a febrile haemorrhagic syndrome should be considered to have a viral haemorrhagic fever until proven otherwise. Patients who meet the criteria for probable CCHF should be admitted to hospital and treated with ribavirin. Appropriate isolation precautions should be immediately initiated.

We aimed to characterize an environmental niche driving the distribution of Crimean-Congo haemorrhagic fever (CCHF) in Turkey, using a georeferenced collection of cases reported between 2003 and 2008 and a set of climate and vegetation features. We used mean monthly air temperatures and Normalized Derived Vegetation Index (NDVI) values, at a resolution of 0·1°, as well as climate features at and below the surface. We computed significant differences in monthly variables between positive and negative sites, within the range of distribution of the tick vector. Seasonal climate (growth season and summer length, accumulated temperatures in winter) and vegetation components (anomalies in NDVI data) were analysed. Fragmentation of habitat was obtained from NDVI monthly data at a resolution of 1 km. Neither single climate or vegetation variables, nor any individual seasonal component, accounted in both space and time for the delineation of areas of disease although accumulated temperatures in winter consistently showed lower values in areas where the disease was reported. Coherent and significant differences between disease-containing and disease-free sites were found when habitat fragmentation and connectivity were examined. High fragmentation and connectivity were unambiguously associated with sites where disease is reported and accounted for the spatial spread of cases in 2003–2008. CCHF cases were always associated with areas of highly fragmented and well-connected patches within the range of the tick vector, while there were no reports from areas with low fragmentation. There was a linear relationship between degree of fragmentation and case incidence. The implications of these findings are discussed with reference to the concept of disease spread through networks of connected spots with high densities of infected vectors and social factors driving different human activities in sites of high fragmentation.