Two Atypical Cases of Hantavirus Infections from Sri Lanka

A Systematic Review of Zoonotic Disease Prevalence in Sri Lanka (2000-2022)

Background: The burden of zoonotic diseases in developing countries is significantly underestimated, influenced by various factors such as misdiagnosis, underreporting, natural disasters, climate change, resource limitations, rapid unplanned urbanization, poverty, animal migration, travel, ecotourism, and the tropical environmental conditions prevalent in the region. Despite Sri Lanka's provision of a publicly funded free health care system, zoonoses still contribute significantly to the burden of communicable diseases in the country. This study serves as a timely and exhaustive systematic review of zoonoses reported over the past 22 years in Sri Lanka. Materials and Methods: This systematic review adhered to the guidelines provided by the "Preferred Reporting Items for Systematic Reviews and Meta-Analyses" (PRISMA) statement. A systematic literature search was conducted between July and September 2022, utilizing the following databases and sources: Google Scholar, PubMed, Cochrane Library, Weekly Epidemiological Reports, and Rabies Statistical Bulletins published by the Ministry of Health, Sri Lanka. Results: From the initial database search, 1,710 articles were identified. After excluding nonzoonotic diseases, duplicated reports, inaccessible articles, and those not meeting the inclusion criteria, 570 reports were evaluated for eligibility. Of these, 91 reports were selected for data extraction, comprising 58 original research articles, 10 case reports, 16 weekly epidemiological reports, and 7 rabies statistical bulletins. Over the study period (2000-2022), 14 parasitic, 7 bacterial, and 7 viral zoonoses have been reported in Sri Lanka. Notably, leptospirosis emerged as the most reported zoonotic disease in the country. Conclusions: In response to these findings, we strongly recommend the implementation of a tailored, country-specific prevention and control program. To achieve this goal effectively, we emphasize the importance of adopting a country-specific "One Health" approach as a comprehensive framework for managing and controlling zoonotic diseases in Sri Lanka.

Hantavirus infection in central Sri Lanka - an unusual clinical presentation: a case report

Hantavirus infections are emerging zoonoses. In Asia, the hantavirus commonly manifests as haemorrhagic fever with renal syndrome (HFRS), apparent with fever, thrombocytopenia and acute kidney injury. There are a few cases with the atypical clinical course with cardiopulmonary symptoms in Asia including Sri Lanka. Here, we report a case of hantavirus infection with an atypical cardiopulmonary syndrome-like illness with serological evidence of the Puumala/Puumala-like virus.

Two decades of chronic kidney disease of unknown aetiology (CKDu) research: Existing evidence and persistent gaps from epidemiological studies in Sri Lanka

BACKGROUND

Chronic Kidney Disease of unknown origin (CKDu) excludes known primary renal conditions or systemic disease (such as diabetes mellitus or hypertension). Prominence of CKDu has been noted for some decades in Sri Lanka, especially among men in particular rural areas, prompting many studies directed towards environmental causation. This article critically reviews relevant primary studies.

METHODS

Articles for this literature review (n = 86) were found by searching Medline, Embase, Global Health and ProQuest databases over 2000-2020 utilizing a standard algorithm. Articles were critiqued according to criteria for diagnosis of CKDu, aetiological agents investigated, analytic methods employed and findings.

RESULTS

Criteria for diagnosis of CKDu varied significantly, including pre-selection by proteinuria, eGFR and biopsy proven interstitial nephritis. Prevalence studies have been largely conducted in the North Central Province, with recent studies demonstrating the presence of CKDu in other regions. Aetiological factors investigated in primary studies included water source, use of agrochemicals, agricultural work, heavy metals, snake bites, ayurvedic medication, heat stress, infectious diseases and usage of tobacco and betel leaf. There is no conclusive evidence for any one aetiological agent despite consistent evidence of distal factors such as male sex, rural residence and farming.

CONCLUSIONS

The current body of evidence for any aetiological agent as the cause of CKDu in Sri Lanka is limited. Further research with stronger study designs is necessary to increase knowledge of aetiology of CKDu in Sri Lanka to identify and eliminate exposure to possible causative agent(s) prior to concluding that the disease is multifactorial.

The correlation between three teleconnections and leptospirosis incidence in the Kandy District, Sri Lanka, 2004-2019

Background

Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals excrete leptospires into the environment via their urine. Survival of leptospires in the environment until they enter into a person and several other factors that influence leptospirosis transmission are dependent upon local weather. Past studies show that rainfall and other weather parameters are correlated with the LI in the Kandy district, Sri Lanka. El Niño Southern Oscillation (ENSO), ENSO Modoki, and the Indian Ocean Dipole (IOD) are teleconnections known to be modulating rainfall in Sri Lanka. There is a severe dearth of published studies on the correlations between indices of these teleconnections and LI.

Methods

We acquired the counts of leptospirosis cases notified and midyear estimated population data of the Kandy district from 2004 to 2019, respectively, from weekly epidemiology reports of the Ministry of Health and Department of Census and Statistics of Sri Lanka. We estimated weekly and monthly LI of Kandy. We obtained weekly and monthly teleconnection indices data for the same period from the National Oceanic and Atmospheric Administration (NOAA) of the USA and Japan Agency for Marine-Earth Science and Technology (JAMSTEC). We performed wavelet time series analysis to determine correlations with lag periods between teleconnection indices and LI time series. Then, we did time-lagged detrended cross-correlation analysis (DCCA) to verify wavelet analysis results and to find the magnitudes of the correlations detected.

Results

Wavelet analysis displayed indices of ENSO, IOD, and ENSO Modoki were correlated with the LI of Kandy with 1.9–11.5-month lags. Indices of ENSO showed two correlation patterns with Kandy LI. Time-lagged DCCA results show all indices of the three teleconnections studied were significantly correlated with the LI of Kandy with 2–5-month lag periods.

Conclusions

Results of the two analysis methods generally agree indicating that ENSO and IOD modulate LI in Kandy by modulating local rainfall and probably other weather parameters. We recommend further studies about the ENSO Modoki and LI correlation in Sri Lanka. Monitoring for extreme teleconnection events and enhancing preventive measures during lag periods can blunt LI peaks that may follow.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41182-021-00325-z.

Two Atypical Cases of Hantavirus Infection: Experience from a Tertiary Care Unit in Sri Lanka

Hantaviruses are a large family of enveloped viruses with two medically important families Cricetidae and Muridae which are known to cause rodent-borne diseases worldwide. Some strains cause clinical syndromes with multiorgan involvement in humans such as hantavirus haemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS), which is also known as hantavirus pulmonary syndrome. Clinical differentiation of this infection from other endemic infections in Sri Lanka such as leptospirosis and rickettsial infections is extremely difficult due to overlapping clinical and epidemiologic features such as exposure to rodents and farming. Here, we report two serologically confirmed cases of hantavirus infection from Sri Lanka with different presentation. The first patient had a combination of HCPS and HFRS. The second patient was treated for HPS complicated with acute respiratory distress syndrome (ARDS). Both had a significant clinical, biochemical, and radiological response with early initiation of corticosteroids. However, further studies are required to assess whether steroids hasten the recovery of severe hantavirus infections. We believe that hantavirus infection is an important emerging disease in the country and should be considered as a differential diagnosis in patients presenting with an acute febrile illness as well as in patients presenting with ARDS. Early diagnosis and prompt treatment improve prognosis.

Atypical case of hantavirus infection in Sri Lanka mimicking leptospirosis: a case report

Background

Hantavirus infection is an emerging zoonotic infection which has two characteristic patterns of presentation: hantavirus pulmonary syndrome and hemorrhagic fever with renal syndrome. The clinical presentation of hantavirus infection closely mimics leptospirosis.

Case presentation

This case report describes a previously apparently well 36-year-old Sri Lankan Sinhalese man who presented with an acute febrile illness with myalgia, with liver involvement in the form of transaminitis, cardiac involvement in the form of myocarditis, acute kidney injury, and pulmonary involvement. He was initially managed as severe leptospirosis with multiorgan dysfunction with antibiotics, steroids, and N-acetyl cysteine. A diagnosis of acute hantavirus infection was made subsequently. He made an uneventful recovery.

Conclusion

Hantavirus infections need to considered in the differential diagnosis of patients presenting with acute febrile illness with multiorgan involvement. Larger studies are needed to evaluate the seroprevalence of hantavirus in Sri Lanka because it could be an emerging serious public health problem.

The correlation between local weather and leptospirosis incidence in Kandy district, Sri Lanka from 2006 to 2015

Background: Leptospirosis is an important public health problem in Sri Lanka. Most people become infected by contact with leptospires in soil and in surface water. Survival of leptospires in the environment depends upon the moisture in soil, humidity, temperature and surface water. Leptospires are spread by flood water and waterways. Therefore, the weather of an area influences the leptospirosis incidence of that area. Objectives: To find out the correlations between the leptospirosis incidence in the district of Kandy, Sri Lanka, and local weather variables and then to explore the utility of the findings. Methods: We gathered data on reported leptospirosis cases in the Kandy district and mid-year population data and calculated weekly incidences for 2006 to 2015. Daily weather data from Katugastota weather station was obtained and converted into weekly data. We plotted time series graphs and observed the correlation between six aggregated weather parameters and leptospirosis incidence. Those weather parameters were rainfall, the count of wet days per week, days with rainfall >100 mm per week, minimum temperature, average temperature and average humidity. Then we looked for correlations between leptospirosis incidence and those weather parameters by performing the wavelet analysis. Results: Our wavelet analysis results show peaks of wet days per week, days with rainfall >100 mm per week, minimum temperature, average temperature and average humidity respectively after 2, 3, 13, 20 and 1 week lags were followed by peaks of leptospirosis incidence. Nadirs (troughs) of rainfall after a week were followed by nadirs of leptospirosis incidence. Conclusions: All weather parameters studied are correlated with local leptospirosis incidence and the climate in Kandy is conducive for leptospirosis transmission. Leptospirosis incidence in the Kandy district is high compared to the national and global incidence. Therefore, leptospirosis preventive work in Kandy deserves more attention, especially during months with favorable weather for leptospirosis transmission. Video abstract Read the transcript Watch the video on Vimeo.

Comparison of autoregressive integrated moving average model and generalised regression neural network model for prediction of haemorrhagic fever with renal syndrome in China: a time-series study

OBJECTIVES

Haemorrhagic fever with renal syndrome (HFRS) is a serious threat to public health in China, accounting for almost 90% cases reported globally. Infectious disease prediction may help in disease prevention despite some uncontrollable influence factors. This study conducted a comparison between a hybrid model and two single models in forecasting the monthly incidence of HFRS in China.

DESIGN

Time-series study.

SETTING

The People's Republic of China.

METHODS

Autoregressive integrated moving average (ARIMA) model, generalised regression neural network (GRNN) model and hybrid ARIMA-GRNN model were constructed by R V.3.4.3 software. The monthly reported incidence of HFRS from January 2011 to May 2018 were adopted to evaluate models' performance. Root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were adopted to evaluate these models' effectiveness. Spatial stratified heterogeneity of the time series was tested by month and another GRNN model was built with a new series.

RESULTS

The monthly incidence of HFRS in the past several years showed a slight downtrend and obvious seasonal variation. A total of four plausible ARIMA models were built and ARIMA(2,1,1) (2,1,1)12 model was selected as the optimal model in HFRS fitting. The smooth factors of the basic GRNN model and the hybrid model were 0.027 and 0.043, respectively. The single ARIMA model was the best in fitting part (MAPE=9.1154, MAE=89.0302, RMSE=138.8356) while the hybrid model was the best in prediction (MAPE=17.8335, MAE=152.3013, RMSE=196.4682). GRNN model was revised by building model with new series and the forecasting performance of revised model (MAPE=17.6095, MAE=163.8000, RMSE=169.4751) was better than original GRNN model (MAPE=19.2029, MAE=177.0356, RMSE=202.1684).

CONCLUSIONS

The hybrid ARIMA-GRNN model was better than single ARIMA and basic GRNN model in forecasting monthly incidence of HFRS in China. It could be considered as a decision-making tool in HFRS prevention and control.