Dengue serotype characterization during the 2022 dengue epidemic in Kathmandu, Nepal
Bibliographic record
Abstract
Nepal witnessed a large dengue outbreak, with >54784 cases as of 31 December 2022, with the highest number of cases reported from the Kathmandu valley (55%).1,2 Kathmandu lies at an altitude of ⁓1400 m above sea level and had been previously spared from large outbreaks of mosquito-borne diseases like dengue.3 In parallel to the massive outbreak amongst the local Nepali population, especially amongst residents of Kathmandu, we noticed travellers acquiring the disease, some of whom were rescued by helicopter from high-altitude trekking areas in the Himalayas. Our study aimed to report the dengue serotypes from patients infected during 2022 in Kathmandu, Nepal. During 12 September–12 October 2022, samples from all patients seen at Canadian International Water and Energy Consultants (CIWEC) Hospital, Kathmandu, Nepal or Sheba Medical Centre, Israel with travel history to Nepal, with initial serology positive for dengue were sent for further molecular evaluation to the Central Virology Laboratory (CVL) at Sheba Medical Centre. At Sheba Medical Centre, serology tests for detecting NS1 antigen, Immunoglobulin M (IgM) and Immunoglobulin G (IgG) antibodies against dengue virus were performed by Dengue Early ELISA (Panbio, Brisbane, Australia) and IgM and IgG antibody capture ELISA (Panbio, Brisbane, Australia). Dengue NS1 antigen and serology testing at CIWEC hospital, Kathmandu, was performed by rapid combo commercial test (Abbott Dengue Duo or CTK Biotech Dengue IgG/IgM Combo kits). Molecular testing for dengue serotypes was carried out at the CVL. Nucleic acid testing was performed after extraction from serum (amongst patients seen in Israel) or from dried blood spots applied on Whatman® qualitative filter paper, Grade 3, a thick medium-speed paper with high retention. A single drop of anticoagulated blood was applied with a 50 μL pipette. The diameter of the blood spots was 0.6–10 mm. The size of punches was 0.4 mm and three punches from a single dried blood spot were used for nucleic acid extraction. Extraction of nucleic acids from filter paper was performed by adding 700 μL of lysis buffer (MagNA Pure LC Total Nucleic Acid Isolation Kit lysis/binding buffer, Roche diagnostics, Germany) to the dried blood spot in a 1.5 mL Eppendorf tube followed by shaking at 400 rpm in room temperature for 30 min. Then, total nucleic acid content was extracted using magLEAD 12gC (Precision System Science Co. Ltd, Japan) in a 50 μL elution buffer. PCR testing was done by Quantitative (q) Reverse Transcription - Polymerase Chain Reaction (RT-PCR) of Dengue virus (DENV)-1–4.4 Positive results were considered up to the Cycle Threshold (Ct) of 40. The diagnosis was considered primary infection in patients with positive NS1 or positive dengue ribonucleic acid (RNA) and negative serum IgG. It was considered secondary infection in patients with positive NS1 or positive dengue RNA and positive serum IgG with negative IgM, or when IgG level was higher than IgM at the first week of infection. Undetermined cases demonstrated both positive IgG and IgM but without quantification of antibodies level (as in the Combo Dengue RDT). Patients were categorized as travellers, expatriates and local Nepalese. Since the data were assessed anonymously, informed consent was waived by the Sheba Medical Centre - Institutional Review Board (IRB) committee. Ethical clearance was obtained from the Nepal Research Health Council as well as the IRB of Sheba Medical Centre. Altogether there were 69 dengue cases, all acquired in Nepal, 66 were likely infected in Kathmandu. In total, 30 were travellers, 11 expatriates and 28 local Nepalese residents. Their median age was 36 (IQR 25–52) years, with the local Nepalese being older (Table 1). The majority were females, 37 (53.6%). Distribution of the different serotypes of Dengue between Nepalese and non-Nepalese patients Six cases of foreigners and two cases of locals were undetermined, and therefore were excluded for this calculation. Ten cases of foreigners and three cases of locals had negative or unavailable PCR results, and therefore were excluded for this calculation. Amongst the cohort of 69 patients, 65 were tested molecularly and 56 were positive. The rest were positive by NS1 or IgM. All were tested for dengue serotype during their febrile illness. Amongst 56 dengue RNA-positive samples, 34 had DEN-1, 17 had DEN-3 and 5 had DEN-2 (Table 1). The Ct values, in the different serotypes, ranged from the cycle of 14.0–40.0, with a median of 27.1 (IQR 24.4–30.3). Evaluating the median viral load for each serotype as indicated by the Ct value, the median value for DEN-1 was 26.7 (IQR 24.5–29.9), DEN-3 25.9 (IQR 23.7–31.0) and 27.8 (IQR 27.5–31.1) for DEN-2. In both groups (Nepalese and non-Nepalese), most patients had primary dengue infection (~92%). There were no fatalities nor any severe dengue. Helicopter rescue from trekking areas was documented in six out of 30 travellers with dengue. This report documents the dengue serotypes circulating in the Kathmandu valley during the 2022 outbreak. The dominant serotypes were DEN-1 and DEN-3. Only five DEN-2 cases were diagnosed, all amongst local Nepalese, who may have been infected outside of Kathmandu valley (e.g. Terai, known to previously have DENV-2).5 The 2019 outbreak in Kathmandu was dominated by DEN-2.5,6 The risk for severe dengue is considered high with a secondary heterologous dengue infection.7 However, in travellers, fatal dengue cases have mainly been reported in primary dengue cases.8 We tried to investigate primary vs. secondary infections in this cohort. Primary infection was dominant amongst travellers, as expected, but amongst locals as well. Although our sample of the local population is tiny, this may indicate that dengue has only recently emerged in the Kathmandu valley. Six patients were helicopter rescued from the Himalayas leading to trip and trek disruption. It is presumed that their infection was acquired in Kathmandu, but due to the incubation period, symptoms started whilst being at a high altitude (above the level of known dengue infection). Any trekker who becomes ill with dengue on the trek will either have to rest where they are until they are better or arrange to be flown out to Kathmandu for diagnostic tests and further care. This illustrates that primary illness might also demand helicopter evacuation even without fulfilling the World Health Organization definition of severe disease. The use of filter paper for molecular diagnosis of DENV RNA has been described previously9 and was used extensively here to characterize the DENV serotypes responsible for the outbreak. In addition to its usefulness for diagnosis, this method is also valuable for epidemiological studies in rural areas or areas without modern laboratories when samples must be stored, shipped and tested only after some time. Since infected Aedes mosquitoes can also spread Zika and Chikungunya, travellers and travel health practitioners must be aware of the risk of mosquito-borne diseases seen now at newer regions and at higher altitudes. Dengue has encroached on this Himalayan nation and future outbreaks are expected. Here, dengue was predominantly serotype 1, followed by 3 and 2. Due to the small sample size in this study relative to the outbreak, the ranking of dengue serotypes by prevalence is unlikely to have external validity. However, multiple serotypes circulating in the same region portend the emergence of more severe dengue disease in Nepal. The authors would like to thank Tej Bahadur Magar, laboratory personnel, the doctors, nurses and staff at CIWEC. Bhawana Amatya (Conceptualization, Design, Writing - original draft preparation, review and editing [lead]), Eli Schwartz (Conceptualization, Design, Data Collection, Writing - original draft preparation and review), Asaf Biber (Data Analysis, Writing - review), Oran Erster (Molecular analysis of the material of sera and filter paper), Yaniv Lustig (Molecular analysis of the material of sera and filter paper), Rashila Pradhan (Conception, Design, Data Collection), Bhawani Khadka (Data Collection), Prativa Pandey (Conception, Design, Supervision, Writing - original draft preparation, review and editing). No funding source to declare. No grants or other financial support. The authors have no conflicts of interest to declare. Dataset is available on request from Zenodo at the following link: https://doi.org/10.5281/zenodo.7774020.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".