Estimating the burden of leptospirosis in Sri Lanka; a systematic review

Eligibility criteria

We recruited studies and reports containing details of possible cases of human leptospirosis originating from Sri Lanka between 1900 and 2017. All types of publications with primary data were included, and no language restrictions were employed. Both published and unpublished research and reports were included.

Databases and information resources

For this review, we performed an Internet-based search using Pub Med, MEDLINE®, BIOSIS Previews, Zoological Record, Web of Science Core Collection, Current Contents Connect, KCI-Korean Journal Database, BIOSIS Citation Index, Data Citation Index and SciELO Citation Index. Google Scholar was used to gather all Internet-based literature not indexed in the above databases because most of the local journals are not indexed in the selected databases, and it is common to have technical reports (usually available in Google Scholar) rather than journal articles in the Sri Lankan setup. In addition, we used four bibliographic references to search for local literature: Bibliography of medical publications related to Sri Lanka 1811–1976 [15] and its supplement Bibliography on health in Sri Lanka, 1977–1980 [16] by Peiris and Uragoda; Bibliography of Medical Literature 1980–2005 compiled by the Post Graduate Institute of Medicine (PGIM) Library, Colombo; and the Annotated Bibliography of dissertations and theses Presented to PGIM by Postgraduate Trainees, published by the PGIM. Further, we searched technical reports published by the Medical Research Institute (MRI), papers published on the Ceylon Medical Journal before 2008 (the CMJ website is available after 2008), archived issues of the Sri Lanka Journal of Medical Sciences and the Kandy Medical Journal in four libraries (Sri Lanka Medical Association Library, PGIM library and Colombo and Peradeniya Medical faculty libraries). Throughout the process, we searched reference lists of selected articles to include missing articles from the main search. For national level data, we used several sources. Quarterly epidemiological bulletin (QEB) data of the epidemiology unit of Sri Lanka and the data published by the epidemiology unit in disease trends (http://www.epid.gov.lk) were compared to obtain the best data set for national “surveillance” data. These surveillance data were from routine notifications from hospitalized patients and outpatients and were considered more “representative” of all cases. The Indoor Morbidity and Mortality Returns (IMMR) available from the Ministry of Health were obtained as “hospital” data. IMMR data are based on diagnoses made during the clinical management at an inward setup. This diagnosis is typically based on clinical criteria and varies widely from physician to physician. IMMR data are limited to hospitalized patients and may represent only moderate to severe cases, as mild patients are treated as outpatients.

Search strategies

The key themes for the search included “Leptospirosis” or “Leptospira” in combination with “Sri Lanka” or “Ceylon”. For the PubMed search, appropriate search terms were identified and translated to MeSH terms where possible. Entry items and keywords used in the initial search related to “Leptospira” are listed in Additional file 2. The PubMed search string used was (“Leptospira”[Title/Abstract]. OR “Leptospirosis”[Title/Abstract]. OR “Weil Disease”[Title/Abstract]. OR “Leptospirosis”[Mesh]. OR “Weil Disease”[Mesh]. OR “Leptospira”[Mesh]) AND (“Ceylon” OR “Sri Lanka”). Other databases were searched through Web of Science, and the search string was TOPIC: (Leptospirosis) OR TOPIC: (Leptospira) OR TOPIC: (Weil’s disease) Refined by: TOPIC: (“Sri Lanka” OR “Ceylon”). The Google Scholar search string used was (“Leptospira”OR “Leptospirosis”OR “Weil’s Disease”) AND (“Ceylon” OR “Sri Lanka”).

Study selection

After removal of duplicates from different databases, the title and abstract were screened to exclude articles that were not relevant. These included articles that were not directly related to leptospirosis, animal studies and articles without primary data. Conference publications were included if the data were not later published as journal articles or technical papers. Full text reviews were performed for all screen-selected articles to further assess the eligibility criteria. Articles reporting diagnosed cases of leptospirosis and deaths due to leptospirosis were included in the final evidence synthesis. For national disease estimates, we included reports with possible cases of leptospirosis.

Data collection process

The data were extracted using an Excel data sheet by two independent investigators (JW and IK), and the extracted dataset was fully reviewed for confirmation by the SA.

Data items

Data items included in this review were used to assess the study and to describe sequelae. These included: study year, authors, duration, study population, sampling procedure, sample size (n), laboratory confirmation, complications and deaths.

Risk of bias

Risk of bias in individual studies was assessed using a checklist (Additional file 3). The main risk of bias assessed was due to the study population. First, we searched the methods to see whether measures were taken to include the full study population. Although different study populations were allowed in this review, we assessed whether systematic inclusion of all leptospirosis patients was done either through population screening (population-based studies) or through febrile patient screening. The risk of selection bias was classified as mild, moderate or high based on this assessment. Bias due to misclassification was assessed by examining the diagnostic criteria. If the diagnosis was confirmed using the laboratory criteria given by the leptospirosis burden epidemiology research group (LERG), it was considered a study with a low risk of bias. Studies with positive screening tests but that were not confirmed as “low risk” were considered “moderate risk”, and studies without laboratory confirmation were considered at “high risk” for bias. Most of the patients recruited to the studies were moderate to severe patients. This resulted in an over estimate of the complication and mortality rates, and there were higher numbers of publications from areas where higher number of researchers were conducting studies. Hence, the risk of bias across studies due to “publication bias” or selective reporting is discussed in the results section.

Data synthesis and estimations

We summarized the data into two main categories: national disease estimates and complications/deaths reported in studies. Construction of 95% confidence limits for observed rates and counts was performed using the Poisson distribution model using the formula \( C\pm {Z}_{1-\propto /2}\sqrt{C} \) for counts and \( R\pm {Z}_{1-\propto /2}\sqrt{\frac{\overline{C}}{n}} \)for rates. Since hospital reported data grossly underestimate the leptospirosis incidence, we added an adjustment factor for disease incidence estimates using published research studies [17]. For this purpose, we searched for studies reporting systematic patient recruitment by screening all febrile patients (low risk for selection bias) together with disaggregated data by type of diagnosis (clinically suspected or not). This was slightly different from the global disease burden estimates that used a robust method of adjustment for underdiagnosis using multicounty data and modelling, which may not be directly applicable for in-country estimation. For Sri Lankan data, the adjustments were done conservatively using the reported under-diagnosed proportion and calculating the 95% confidence intervals for the proportion using the original data. Using these estimated proportions, we calculated high and low estimates for the caseload in each year. For case fatality rate calculations, we used studies with more than 100 confirmed cases (to reduce the chance of error), in which data were collected in defined settings over a period of at least 3 months. We calculated the pooled case fatality rate with 95% CI using the Poisson distribution model.

National disease incidence estimate

The reasons for increased incidence after 2008 are not well understood. However, we believe that the increased awareness among treating physicians after the outbreak in 2008 contributed to enhanced reporting in subsequent years.

Estimated caseload, disease incidence and deaths due to leptospirosis

Data from a single study were available to calculate the hospital underestimation of cases. In the study in Kegalle in 2008, 26 probable cases fulfilling the surveillance criteria were treated as other diseases (hence not included in IMMR), while 175 patients were documented as having leptospirosis during the same period [17]. We used these numbers to estimate the annual caseload with the upper limit of 95% confidence interval for the estimates. After the adjustments, the estimated annual caseload of leptospirosis was 10,423, and the cumulative incidence of leptospirosis that required hospitalization in Sri Lanka during 2008–15 was 52.12 (95% CI 51.69–52.57) per 100,000 people per year (Fig. 2).

Even though leptospirosis was declared a notifiable disease in 1991, major attention was paid to leptospirosis after the heavy outbreak reported in 2008 [18]. Deaths due to leptospirosis were reported in surveillance reports only after this outbreak. However, the number of deaths due to leptospirosis from 2004 to 2008 was available in QEB of the 1st quarter in 2009. Neither surveillance data nor hospital data were based on confirmed cases of leptospirosis but rather were based on suspected patients of leptospirosis. Applying the reported case fatality rate from hospitals to the estimated caseload, the estimated number of annual hospital deaths due to leptospirosis was approximately 311 (95% CI 277–347) (Fig. 2).

Complications and organ involvement

Deaths, causes of death and case fatality rates based on individual studies

No publications assessed the mortality rates of Sri Lanka. However, we recruited studies with data on deaths after assessment for risk of bias. None of the articles reported the true mortality rate, as the sample selection was biased towards the objective of each particular study. Hence, the generalizability of death rates is limited.

The highest death rates were reported from studies performed among Intensive care unit (ICU) patients. At General Hospital Kaluthara, 20 deaths out of 45 ICU patients confirmed for leptospirosis were reported, with a case fatality rate of 44.4% [19]. A study done among ICU patients at National Hospital of Sri Lanka reported a Case Fatality Rate (CFR) of 33.3%. Among usual ward settings, the highest death rate was from Teaching Hospital Peradeniya, with 33 deaths of 227 patients (CFR 14.5%) [20], followed by a study done in 1974 with a CFR of 11.7% [21]. However, in both these studies, there was no information on whether the investigators recruited all cases of leptospirosis through systematic patient enrolment. For CFR estimation, we included only three studies with more than 100 confirmed cases. The estimated pooled CFR was 7.0% (95% CI 5.2–9.4). Based on this CFR, the estimated annual death toll due to leptospirosis in Sri Lanka is approximately 730 (95% CI 542–980).