RESUMEN
BACKGROUND: Late-relapsing hepatitis after yellow fever (LHep-YF) during the convalescent phase of the disease has been described during recent yellow fever (YF) outbreaks in Brazil. LHep-YF is marked by a rebound in liver enzymes and nonspecific clinical manifestations around 46-60 days after YF symptom onset. METHODS: Here we have characterized the clinical course and risk factors for LHep-YF using data from a representative cohort of patients who survived YF in Brazil, 2017-2018. A total of 221 YF-positive patients were discharged from the infectious disease reference hospital in Minas Gerais and were followed up at 30, 45, and 60 days post-symptom onset. RESULTS: From 46 to 60 days post-symptom onset, 16% of YF patients (n = 36/221) exhibited a rebound of aminotransferases (aspartate aminotransferase or alanine aminotransferase >500 IU/L), alkaline phosphatase, and total bilirubin levels. Other etiologies of liver inflammation such as infectious hepatitis, autoimmune hepatitis, and metabolic liver disease were ruled out. Jaundice, fatigue, headache, and low platelet levels were associated with LHep-YF. Demographic factors, clinical manifestations, laboratory tests, ultrasound findings, and viral load during the acute phase of YF were not associated with the occurrence of LHep-YF. CONCLUSIONS: These findings provide new data on the clinical course of Late-relapsing hepatitis during the convalescent phase of YF and highlight the need for extended patient follow-up after acute YF.
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Hepatitis A , Hepatitis , Vacuna contra la Fiebre Amarilla , Fiebre Amarilla , Humanos , Fiebre Amarilla/complicaciones , Fiebre Amarilla/epidemiología , Brotes de Enfermedades , Factores de Riesgo , Hepatitis/epidemiología , Hepatitis A/epidemiología , Brasil/epidemiología , Progresión de la EnfermedadRESUMEN
BACKGROUND: Malaria in coastal Kenya shows spatial heterogeneity and seasonality, which are important factors to account for when planning an effective control system. Routinely collected data at health facilities can be used as a cost-effective method to acquire information on malaria risk for large areas. Here, data collected at one specific hospital in coastal Kenya were used to assess the ability of such passive surveillance to capture spatiotemporal heterogeneity of malaria and effectiveness of an augmented control system. METHODS: Fever cases were tested for malaria at Msambweni sub-County Referral Hospital, Kwale County, Kenya, from October 2012 to March 2015. Remote sensing data were used to classify the development level of each monitored community and to identify the presence of rice fields nearby. An entomological study was performed to acquire data on the seasonality of malaria vectors in the study area. Rainfall data were obtained from a weather station located in proximity of the study area. Spatial analysis was applied to investigate spatial patterns of malarial and non-malarial fever cases. A space-time Bayesian model was performed to evaluate risk factors and identify locations at high malaria risk. Vector seasonality was analysed using a generalized additive mixed model (GAMM). RESULTS: Among the 25,779 tested febrile cases, 28.7 % were positive for Plasmodium infection. Malarial and non-malarial fever cases showed a marked spatial heterogeneity. High risk of malaria was linked to patient age, community development level and presence of rice fields. The peak of malaria prevalence was recorded close to rainy seasons, which correspond to periods of high vector abundance. Results from the Bayesian model identified areas with significantly high malaria risk. The model also showed that the low prevalence of malaria recorded during late 2012 and early 2013 was associated with a large-scale bed net distribution initiative in the study area during mid-2012. CONCLUSIONS: The results indicate that the use of passive surveillance was an effective method to detect spatiotemporal patterns of malaria risk in coastal Kenya. Furthermore, it was possible to estimate the impact of extensive bed net distribution on malaria prevalence among local fever cases over time. Passive surveillance based on georeferenced malaria testing is an important tool that control agencies can use to improve the effectiveness of interventions targeting malaria (and other causes of fever) in such high-risk locations.
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Monitoreo Epidemiológico , Hospitales , Malaria/epidemiología , Topografía Médica , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Niño , Preescolar , Femenino , Humanos , Lactante , Recién Nacido , Kenia , Masculino , Persona de Mediana Edad , Estudios Prospectivos , Medición de Riesgo , Estaciones del Año , Análisis Espacio-Temporal , Adulto JovenRESUMEN
Aedes aegypti is the primary vector of dengue fever virus (DENV) worldwide. Infusions made from organic materials have been shown to act as oviposition attractants for Ae. aegypti; however, studies on locally suitable infusion materials are lacking. The current study assessed the suitability of 4 locally available materials as oviposition infusions for use in surveillance and control of Ae. aegypti in Kwale County, Kenya. Oviposition infusion preferences were assessed in laboratory, semifield, and field conditions, using 4 infusions made from banana, grass, neem, and coconut. In addition, ovitrapping in wall, grass, bush, and banana microhabitats was done in 10 houses each in urban and rural coastal households to determine suitable oviposition microhabitats. Overall, the highest oviposition responses were observed for banana infusion, followed by neem and grass infusions, which were comparable. Coconut infusion resulted in the lowest oviposition response. Although female Ae. aegypti did not show preference for any microhabitat, the oviposition activity across all the microhabitats was highly enhanced by use of the organic infusions. Banana, neem, and grass infusions could be used to attract gravid mosquitoes to oviposition sites laced with insecticide to kill eggs. Additionally, banana plantings could be important targets for integrated vector control programs.
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Aedes , Dengue , Insecticidas , Femenino , Animales , Aedes/fisiología , Mosquitos Vectores , Oviposición , Kenia/epidemiología , PoaceaeRESUMEN
BACKGROUND: Aedes aegypti, the principal vector for dengue and other emerging arboviruses, breeds preferentially in various man-made and natural container habitats. In the absence of vaccine, epidemiological surveillance and vector control remain the best practices for preventing dengue outbreaks. Effective vector control depends on a good understanding of larval and adult vector ecology of which little is known in Kenya. In the current study, we sought to characterize breeding habitats and establish container productivity profiles of Ae. aegypti in rural and urban sites in western and coastal Kenya. METHODS: Twenty sentinel houses in each of four study sites (in western and coastal Kenya) were assessed for immature mosquito infestation once a month for a period of 24 months (June 2014 to May 2016). All water-holding containers in and around the households were inspected for Ae. aegypti larvae and pupae. RESULTS: Collections were made from a total of 22,144 container visits: Chulaimbo (7575) and Kisumu (8003) in the west, and from Msambweni (3199) and Ukunda (3367) on the coast. Of these, only 4-5.6% were positive for Ae. aegypti immatures. In all four sites, significantly more positive containers were located outdoors than indoors. A total of 17,537 Ae. aegypti immatures were sampled from 10 container types. The most important habitat types were buckets, drums, tires, and pots, which produced over 75% of all the pupae. Key outdoor containers in the coast were buckets, drums and tires, which accounted for 82% of the pupae, while pots and tires were the only key containers in the western region producing 70% of the pupae. Drums, buckets and pots were the key indoor containers, producing nearly all of the pupae in the coastal sites. No pupae were collected indoors in the western region. The coastal region produced significantly more Ae. aegypti immatures than the western region both inside and outside the sentinel houses. CONCLUSIONS: These results indicate that productive Ae. aegypti larval habitats are abundant outdoors and that only a few containers produce a majority of the pupae. Although the numbers were lower, productive habitats were detected within households. Targeting source reduction efforts towards these productive containers both inside and outside homes is likely to be a cost-effective way to reduce arboviral transmission in these regions.