Dengue and leptospirosis infection during the coronavirus 2019 outbreak in Sri Lanka

Niriella, Madunil Anuk; Ediriweera, Dileepa Senajith; Silva, A P De; Premarathna, B H R; Jayasinghe, Saroj; Silva, H J de

doi:10.1093/trstmh/trab058

Cited by 19 publications

(16 citation statements)

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“…Held et al (2005) demonstrate that the joint modelling approach on multiple diseases achieves a gain in precision of the RR estimates. Niriella et al (2021) spot a sharp decrease in dengue hospitalisations for the second quarter of 2020 compared with pre-COVID-19 peaks in Sri Lanka. The drastic measures imposed by the Sri Lanka government regarding COVID-19 outbreaks help the reduction of dengue hospitalisations.…”

Section: Discussionmentioning

confidence: 90%

Spatio-temporal detection for dengue outbreaks in the Central Region of Malaysia using climatic drivers at mesoscale and synoptic scale

Yip

Him

Jamil

et al. 2021

Preprint

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Background: The disease dengue is associated with both mesoscale and synoptic scale meteorology. Previous studies of this disease, especially for south-east Asia, have found very limited association between synoptic meteorological variables and the number of dengue hospitalisations. However, to tackle future severe outbreaks and to institute an early warning system, it will immensely beneficial to find and establish more clear association with rate of dengue hospitalisations and the most relevant meteorological variables. Objectives: A rigorous Bayesian modelling framework is provided to identify the most important meteorological covariates and their lagged effects for developing an early warning system for dengue outbreaks in the Central Region of Malaysia. Method: We obtain the dengue hospitalisations count data and the demographic information in the Central Region of Malaysia. Along with other mesoscale environmental measurements such as local temperature, precipitation and ozone concentration level, we also examine multiple synoptic scale Ni&ntildeo indices which are related to the phenomenon of El Ni&ntildeo Southern Oscillation and an unobserved meteorological variable derived from reanalysis data. A probabilistic early warning system is built based on a Bayesian spatio-temporal hierarchical model with a physically interpretable complex structure. Results: Our study finds a 46.87\% of increase in dengue hospitalisations due to one degree increase in the sea surface temperature anomalies in the central equatorial Pacific region with a lag time of six weeks. We also discover the existence of a mild association between the rate of cases and a distant lagged cooling effect of 28 weeks related to a phenomenon called El Ni&ntildeo Modoki. The proposed model also observes significant amount of association with some other meteorological parameters with disease rates. These associations are assessed by using an optimal Bayesian spatio-temporal model that outperforms other candidate models in terms of estimated out-of-sample predictive accuracy and performance in correctly issuing the warnings early. Discussion: With the novel spatial dynamic early warning system presented, our results show that the synoptic meteorological drivers can enhance short-term detection of dengue outbreaks and these can also potentially be used to provide longer-term forecasts

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Section: Discussionmentioning

confidence: 90%

Spatio-temporal detection for dengue outbreaks in the Central Region of Malaysia using climatic drivers at mesoscale and synoptic scale

Yip

Him

Jamil

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…In Sri Lanka, a reduction of 73.6% of confirmed cases of dengue between 2019 and 2020 was reported. Several factors may be triggered by these results, including weather conditions, the fear of hospitals due to the risk of hospital-acquired COVID-19 infection, and the closure of schools, offices, and airports during lockdowns [30].…”

Section: Discussionmentioning

confidence: 99%

Double Trouble: Dengue Followed by COVID-19 Infection Acquired in Two Different Regions: A Doctor’s Case Report and Spatial Distribution of Cases in Presidente Prudente, São Paulo, Brazil

et al. 2021

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Co-epidemics of COVID-19 and dengue in dengue-endemic countries represent a serious public health concern. In Brazil, São Paulo state ranks first for cases and deaths from COVID-19, and dengue is endemic in most regions of the country. In 2020, an outbreak of dengue occurred in western São Paulo. We determined the spatiotemporal distribution of dengue in the context of COVID-19 cases in Presidente Prudente, a mid-sized city in western São Paulo. To illustrate the burden of both infections, a case report of a doctor and his family, infected with dengue and COVID-19, is presented. There were three clusters of dengue and COVID-19 in the periphery. A dengue cluster was found in a region where there were no corresponding COVID-19 cases. Meanwhile, there were COVID-19 clusters where dengue activity was lower. In 2020, the COVID-19 epidemic emerged when dengue reached its seasonal peak, resulting in a simultaneous outbreak of both diseases. Lower rates of dengue were found in the city compared with 2019, and the fear of patients with mild dengue symptoms about remaining in hospital and acquiring COVID-19 infection may be the main cause. Simultaneous spatial clusters of dengue and COVID-19 in environmentally and socioeconomically vulnerable areas can guide public health authorities in intensive interventions to improve clinical diagnosis, epidemiological surveillance, and management of both diseases. The patient and his family were first infected with dengue and he then carried COVID-19 to his family, reinforcing the risk of health care workers spreading the virus to the community. We highlight the epidemiological significance of presenting a case report and spatial analysis of COVID-19 in the same study in the context of a dengue outbreak.

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“…The impact of COVID-19 containment measures on the incidence of dengue has been variable with reports of increases in Thailand and Singapore [19,20] but a decrease in Malaysia [13]. Data from the second quarter of 2020 suggested that the incidence of dengue decreased in Sri Lanka during this period [21]. Our results for the whole of the lockdown period from March 2020 to December 2020 and rst quarter of 2021 nationwide and district-wise, show a signi cant decrease in reported number of dengue cases compared with predictions based on the preceding ve pre-pandemic years.…”

Section: Discussionmentioning

confidence: 99%

Reduced Dengue Incidence During COVID-19 Restrictions in Sri Lanka From March 2020 to April 2021

Surendran

Ratnarajah

Sivabalakrishnan

et al. 2021

Preprint

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BackgroundDengue is a major public health concern in Sri Lanka. COVID-19 in Sri Lanka was first detected in January 2020, and has continued to be prevalent in the country since that time. The impact of public health measures imposed to restrict COVID-19 transmission on the incidence of dengue throughout the island and particularly its northern Jaffna district in the period March 2020 to April 2021 was determined.MethodsThe incidence of dengue and COVID-19, rainfall and the public health measures implemented to contain COVID-19 transmission for each district in Sri Lanka were obtained from Government sources. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to predict the dengue incidence expected in March 2020 to April 2021, based on pre-pandemic data and this was compared with the actual reported incidence of dengue during the period of COVID-19 restrictions. Ovitrap collections of Aedes larvae were also carried out in the Gurunagar ward of Jaffna city in the Jaffna district during the 2020 and 2021 lockdown and the findings compared with data from 2019.ResultsThe reported number of dengue cases for the whole country from March 2020 to April 2021 was significantly lower than the numbers of dengue cases predicted from the five years immediately preceding the COVID-19 pandemic (2015-2019). Decreased numbers of dengue cases were reported compared to predicted numbers of cases in all 25 administrative districts in the country including the Jaffna district. Aedes larval numbers collected from ovitraps in the Gurunagar ward in Jaffna city during the COVID-19 lockdown period were decreased, with significantly lower proportions of Ae. aegypti than Ae. albopictus, compared with 2019. ConclusionPublic health measures that restricted movement of people, closed schools, universities and offices in order to contain COVID-19 transmission unexpectedly led to a marked reduction in the incidence of dengue in Sri Lanka, in contrast to Singapore. The differences between the two tropical islands have significant implications for the epidemiology of dengue.

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Dengue and leptospirosis infection during the coronavirus 2019 outbreak in Sri Lanka

Cited by 19 publications

References 1 publication

Spatio-temporal detection for dengue outbreaks in the Central Region of Malaysia using climatic drivers at mesoscale and synoptic scale

Spatio-temporal detection for dengue outbreaks in the Central Region of Malaysia using climatic drivers at mesoscale and synoptic scale

Double Trouble: Dengue Followed by COVID-19 Infection Acquired in Two Different Regions: A Doctor’s Case Report and Spatial Distribution of Cases in Presidente Prudente, São Paulo, Brazil

Reduced Dengue Incidence During COVID-19 Restrictions in Sri Lanka From March 2020 to April 2021

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