Crimean-Congo hemorrhagic fever (CCHF) is an arthropod-borne disease of humans associated with a severe clinical picture, including hemorrhagic syndrome and a high mortality rate. CCHF virus is widely distributed throughout large areas of the world. To characterize the serological status in CCHF patients, paired clinical samples were collected from suspected CCHF patients and analyzed by microbiological and other laboratory analyses with the aim of: determining the presence of neutralizing antibodies against CCHF virus; investigating the cross-reactivity of these neutralizing antibodies against virus isolated from the same outbreak and against other available laboratory strain; and studying the relationship between the isolated virus with other virus by whole genome sequencing. Patients at Boo-Ali Hospital, Zahedan, Iran, with clinical symptoms ranging from mild to severe hemorrhagic fever were included in the study. Two serum samples were taken from each patient, the first as soon as the patient matched the criteria for CCHF notification and the second when the patient was discharged from hospital (2 weeks later). Commercial and in-house assays revealed a positive IgM signal in acute serum samples from six patients. A novel finding was that CCHF patients develop neutralizing antibodies soon after infection. Interestingly these antibodies were able to neutralize other CCHF virus strains too. The complete sequence of the Zahedan 2007 isolate, including the hitherto unknown first L-segment sequence, was identified using an original clinical sample from one patient with confirmed CCHF infection.
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Sci Rep
December 2024
Public Health and community medicine Department, Theodor Bilharz Research Institute, Helwan University, Cairo, Egypt.
Infectious diseases significantly impact both public health and economic stability, underscoring the critical need for precise outbreak predictions to effictively mitigate their impact. This study applies advanced machine learning techniques to forecast outbreaks of Dengue, Chikungunya, and Zika, utilizing a comprehensive dataset comprising climate and socioeconomic data. Spanning the years 2007 to 2017, the dataset includes 1716 instances characterized by 27 distinct features.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Genetics, University of Cambridge, Cambridge CB23EH, United Kingdom.
Uncovering rates at which susceptible individuals become infected with a pathogen, i.e., the force of infection (FOI), is essential for assessing transmission risk and reconstructing distribution of immunity in a population.
View Article and Find Full Text PDFPLoS One
December 2024
Excellent Center for Dengue and Community Public Health (EC for DACH), Walailak University, Nakhon Si Thammarat, Thailand.
One of the consequences of the COVID-19 lockdown is that it hinders school-based dengue management interventions. This is due to the closure of schools and the limited availability of online lessons in certain schools. Conversely, the level of basic understanding that primary school children have about the condition is directly related to their likelihood of getting it and their ability to modify their behaviour to prevent it.
View Article and Find Full Text PDFMymensingh Med J
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Dr Sadia Khanduker, Associate Professor, Department of Biochemistry, Bangladesh Medical College, Dhaka, Bangladesh; E-mail:
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View Article and Find Full Text PDFSci Rep
December 2024
Bangladesh Institute of Governance and Management, Dhaka, 1207, Bangladesh.
Dengue, a mosquito-borne viral disease, continues to pose severe risks to public health and economic stability in tropical and subtropical regions, particularly in developing nations like Bangladesh. The necessity for advanced forecasting mechanisms has never been more critical to enhance the effectiveness of vector control strategies and resource allocations. This study formulates a dynamic data pipeline to forecast dengue incidence based on 13 meteorological variables using a suite of state-of-the-art machine learning models and custom features engineering, achieving an accuracy of 84.
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