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Fulltext Co-distribution and co-infection of chikungunya and dengue viruses

Furuya-Kanamori L, Liang S, Milinovich G, Soares Magalhaes RJ, Clements AC, Hu W, et al.

BMC Infect Dis, 2016;16:84.
PMID: 26936191 DOI: 10.1186/s12879-016-1417-2

BACKGROUND: Chikungunya and dengue infections are spatio-temporally related. The current review aims to determine the geographic limits of chikungunya, dengue and the principal mosquito vectors for both viruses and to synthesise current epidemiological understanding of their co-distribution.
METHODS: Three biomedical databases (PubMed, Scopus and Web of Science) were searched from their inception until May 2015 for studies that reported concurrent detection of chikungunya and dengue viruses in the same patient. Additionally, data from WHO, CDC and Healthmap alerts were extracted to create up-to-date global distribution maps for both dengue and chikungunya.
RESULTS: Evidence for chikungunya-dengue co-infection has been found in Angola, Gabon, India, Madagascar, Malaysia, Myanmar, Nigeria, Saint Martin, Singapore, Sri Lanka, Tanzania, Thailand and Yemen; these constitute only 13 out of the 98 countries/territories where both chikungunya and dengue epidemic/endemic transmission have been reported.
CONCLUSIONS: Understanding the true extent of chikungunya-dengue co-infection is hampered by current diagnosis largely based on their similar symptoms. Heightened awareness of chikungunya among the public and public health practitioners in the advent of the ongoing outbreak in the Americas can be expected to improve diagnostic rigour. Maps generated from the newly compiled lists of the geographic distribution of both pathogens and vectors represent the current geographical limits of chikungunya and dengue, as well as the countries/territories at risk of future incursion by both viruses. These describe regions of co-endemicity in which lab-based diagnosis of suspected cases is of higher priority.
Erratum: Furuya-Kanamori L, Liang S, Milinovich G, Magalhaes RJ, Clements AC, Hu W, Brasil P, Frentiu FD, Dunning R, Yakob L. Erratum to: Co-distribution and co-infection of chikungunya and dengue viruses. BMC Infect Dis. 2016 Apr 29;16:188. doi: 10.1186/s12879-016-1519-x. PubMed PMID: 27129475; PubMed Central PMCID: PMC4851825.
Fulltext Clinical evaluation of dengue and identification of risk factors for severe disease: protocol for a multicentre study in 8 countries

Jaenisch T, Tam DT, Kieu NT, Van Ngoc T, Nam NT, Van Kinh N, et al.

BMC Infect Dis, 2016 Mar 11;16:120.
PMID: 26968374 DOI: 10.1186/s12879-016-1440-3

The burden of dengue continues to increase globally, with an estimated 100 million clinically apparent infections occurring each year. Although most dengue infections are asymptomatic, patients can present with a wide spectrum of clinical symptoms ranging from mild febrile illness through to severe manifestations of bleeding, organ impairment, and hypovolaemic shock due to a systemic vascular leak syndrome. Clinical diagnosis of dengue and identification of which patients are likely to develop severe disease remain challenging. This study aims to improve diagnosis and clinical management through approaches designed a) to differentiate between dengue and other common febrile illness within 72 h of fever onset, and b) among patients with dengue to identify markers that are predictive of the likelihood of evolving to a more severe disease course.
Fulltext Early diagnostic indicators of dengue versus other febrile illnesses in Asia and Latin America (IDAMS study): a multicentre, prospective, observational study

Rosenberger KD, Phung Khanh L, Tobian F, Chanpheaktra N, Kumar V, Lum LCS, et al.

Lancet Glob Health, 2023 Mar;11(3):e361-e372.
PMID: 36796983 DOI: 10.1016/S2214-109X(22)00514-9

BACKGROUND: Improvements in the early diagnosis of dengue are urgently needed, especially in resource-limited settings where the distinction between dengue and other febrile illnesses is crucial for patient management.
METHODS: In this prospective, observational study (IDAMS), we included patients aged 5 years and older with undifferentiated fever at presentation from 26 outpatient facilities in eight countries (Bangladesh, Brazil, Cambodia, El Salvador, Indonesia, Malaysia, Venezuela, and Viet Nam). We used multivariable logistic regression to investigate the association between clinical symptoms and laboratory tests with dengue versus other febrile illnesses between day 2 and day 5 after onset of fever (ie, illness days). We built a set of candidate regression models including clinical and laboratory variables to reflect the need of a comprehensive versus parsimonious approach. We assessed performance of these models via standard measures of diagnostic values.
FINDINGS: Between Oct 18, 2011, and Aug 4, 2016, we recruited 7428 patients, of whom 2694 (36%) were diagnosed with laboratory-confirmed dengue and 2495 (34%) with (non-dengue) other febrile illnesses and met inclusion criteria, and were included in the analysis. 2703 (52%) of 5189 included patients were younger than 15 years, 2486 (48%) were aged 15 years or older, 2179 (42%) were female and 3010 (58%) were male. Platelet count, white blood cell count, and the change in these variables from the previous day of illness had a strong association with dengue. Cough and rhinitis had strong associations with other febrile illnesses, whereas bleeding, anorexia, and skin flush were generally associated with dengue. Model performance increased between day 2 and 5 of illness. The comprehensive model (18 clinical and laboratory predictors) had sensitivities of 0·80 to 0·87 and specificities of 0·80 to 0·91, whereas the parsimonious model (eight clinical and laboratory predictors) had sensitivities of 0·80 to 0·88 and specificities of 0·81 to 0·89. A model that includes laboratory markers that are easy to measure (eg, platelet count or white blood cell count) outperformed the models based on clinical variables only.
INTERPRETATION: Our results confirm the important role of platelet and white blood cell counts in diagnosing dengue, and the importance of serial measurements over subsequent days. We successfully quantified the performance of clinical and laboratory markers covering the early period of dengue. Resulting algorithms performed better than published schemes for distinction of dengue from other febrile illnesses, and take into account the dynamic changes over time. Our results provide crucial information needed for the update of guidelines, including the Integrated Management of Childhood Illness handbook.
FUNDING: EU's Seventh Framework Programme.
TRANSLATIONS: For the Bangla, Bahasa Indonesia, Portuguese, Khmer, Spanish and Vietnamese translations of the abstract see Supplementary Materials section.

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