Epidemiology of acute febrile illness in Latin America

Moreira, José; Bressan, Clarisse; Brasil, Patrícia; Siqueira, André

doi:10.1016/j.cmi.2018.05.001

Cited by 65 publications

(59 citation statements)

References 62 publications

(51 reference statements)

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“…Fever, lethargy, and arthralgia are common [1,13] and acute febrile illness is a typical manifestation for many patients. In Latin America, DENV, CHIKV, and ZIKV are the three most common infections among acute febrile illness patients [14]. Moreover, co-infection is common if multiple viruses are circulating [13].…”

Section: Introductionmentioning

confidence: 99%

Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection

et al. 2020

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Background Dengue, chikungunya, and Zika are arboviruses of major global health concern. Decisions regarding the clinical management of suspected arboviral infection are challenging in resource-limited settings, particularly when deciding on patient hospitalization. The objective of this study was to determine if hospitalization of individuals with suspected arboviral infections could be predicted using subject intake data. Methodology/Principal findings Two prediction models were developed using data from a surveillance study in Machala, a city in southern coastal Ecuador with a high burden of arboviral infections. Data were obtained from subjects who presented at sentinel medical centers with suspected arboviral infection (November 2013 to September 2017). The first prediction model-called the Severity Index for Suspected Arbovirus (SISA)-used only demographic and symptom data. The second prediction model-called the Severity Index for Suspected Arbovirus with Laboratory (SISAL)-incorporated laboratory data. These models were selected by comparing the prediction ability of seven machine learning algorithms; the area under the receiver operating characteristic curve from the prediction of a test dataset was used to

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Section: Introductionmentioning

confidence: 99%

Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection

et al. 2020

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“…Dengue is a major public health concern with up to 3.9 billion people in 128 countries at risk of the disease (Moreira et al, 2018;Brady et al, 2012). It is the most rapidly spreading mosquito-borne viral disease, with a 30-fold increase in global incidence over the past five decades (World Health Organization, 2012).…”

Section: Introductionmentioning

confidence: 99%

Dengue diagnosis in an endemic area of Peru: Clinical characteristics and positive frequencies by RT-PCR and serology for NS1, IgM, and IgG

Palomares-Reyes

Silva-Caso

Valle

et al. 2019

International Journal of Infectious Diseases

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Background: Huánuco is a central eastern region of Peru whose geography includes high forest and low jungle, as well as a mountain range that constitutes the inter-Andean valleys. It is considered a region endemic for dengue due to the many favorable conditions that facilitate transmission of the virus. Methods: A total of 268 serum samples from patients in Huánuco, Peru with an acute febrile illness were assessed for the presence of dengue virus (DENV) via RT-PCR and NS1, IgM, and IgG ELISA during December 2015 and March 2016. Results: DENV was detected in 25% of samples via RT-PCR, 19% of samples by NS1 antigen ELISA, and 10.5% of samples by IgM ELISA. DENV IgG was detected in 15.7% of samples by ELISA. The most frequent symptoms associated with fever across all groups were headache, myalgia, and arthralgia, with no significant difference between the four test methods Conclusions: In this study, DENV was identified in up to 25% of the samples using the standard laboratory method. In addition, a correlation was established between the frequency of positive results and the serological tests that determine NS1, IgM, and IgG. There is an increasing need for point-of-care tests to strengthen epidemiological surveillance in Peru.

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“…3 Acute febrile illness etiologies such as malaria and dengue, which carry high morbidity and mortality and are of considerable public health interest, thus become the focus of many diagnostic clinical laboratories. 4 Other diseases implicated in AFI may consequently be underdiagnosed and inappropriately managed. 2 The contribution of respiratory viruses to global AFI burden is not well described in the literature.…”

Section: Introductionmentioning

confidence: 99%

Respiratory Viral Infection: An Underappreciated Cause of Acute Febrile Illness Admissions in Southern Sri Lanka

Tillekeratne

Bodinayake

Simmons³

et al. 2019

The American Journal of Tropical Medicine and Hygiene

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The contribution of respiratory viruses to acute febrile illness (AFI) burden is poorly characterized. We describe the prevalence, seasonality, and clinical features of respiratory viral infection among AFI admissions in Sri Lanka. We enrolled AFI patients ³ 1 year of age admitted to a tertiary care hospital in southern Sri Lanka, June 2012-October 2014. We collected epidemiologic/clinical data and a nasal or nasopharyngeal sample that was tested using polymerase chain reaction (Luminex NxTAG, Austin, TX). We determined associations between weather data and respiratory viral activity using the Spearman correlation and assessed respiratory virus seasonality using a Program for Appropriate Technology definition. Bivariable and multivariable regression analyses were conducted to identify features associated with respiratory virus detection. Among 964 patients, median age was 26.2 years (interquartile range 14.6-39.9) and 646 (67.0%) were male. One-fifth (203, 21.1%) had respiratory virus detected: 13.9% influenza, 1.4% human enterovirus/ rhinovirus, 1.4% parainfluenza virus, 1.1% respiratory syncytial virus, and 1.1% human metapneumovirus. Patients with respiratory virus identified were younger (median 9.8 versus 27.7 years, P < 0.001) and more likely to have respiratory signs and symptoms. Influenza A and respiratory viral activity peaked in February-June each year. Maximum daily temperature was associated with influenza and respiratory viral activity (P = 0.03 each). Patients with respiratory virus were as likely as others to be prescribed antibiotics (55.2% versus 52.6%, P = 0.51), and none reported prior influenza vaccination. Respiratory viral infection was a common cause of AFI. Improved access to vaccines and respiratory diagnostics may help reduce disease burden and inappropriate antibiotic use.

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Epidemiology of acute febrile illness in Latin America

Cited by 65 publications

References 62 publications

Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection

Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection

Dengue diagnosis in an endemic area of Peru: Clinical characteristics and positive frequencies by RT-PCR and serology for NS1, IgM, and IgG

Respiratory Viral Infection: An Underappreciated Cause of Acute Febrile Illness Admissions in Southern Sri Lanka

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