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Abstract Nipah virus (NiV) is a zoonotic, single-stranded RNA virus from the family Paramyxoviridae, genus Henipavirus. NiV is a biosafety-level-4 pathogen that is mostly spread by Pteropus species, which serve as its natural reservoir host. NiV is one of the major public health challenges in South and South East Asia. However, few molecular studies have been conducted to characterise NiV in a specific region. The main objective of this review is to understand the epidemiology, pathogenesis, molecular surveillance, transmission dynamics, genetic diversity, reservoir host, clinical characteristics, and phylogenetics of NiV. South and South East Asian nations have experienced NiV outbreaks. Phylogenetic analysis confirmed that two primary clades of NiV are in circulation. In humans, NiV causes severe respiratory illness and/or deadly encephalitis. NiV is mainly diagnosed by ELISA along with PCR. Therefore, we recommend that the governments of the region support the One Health approach to reducing the risk of zoonotic disease transmission in their respective countries.

Abstract Background Cutaneous leishmaniasis (CL) is endemic in 70 countries worldwide. Nepal is considered non-endemic for CL and hence the control program is targeted to visceral leishmaniasis (VL) only. Here, we report the emergence of CL cases in different parts of Nepal. Methods We analyzed the CL and VL cases reported to Epidemiology and Diseases Control Division (EDCD), Ministry of Health and Population, Nepal through District Health Information System 2 (DHIS-2) and Early Warning and Reporting System (EWRS) during the past 4 years (2016–2019). Any laboratory-confirmed case was included in the study. Demographic and clinical details of each patient were transcribed into Excel sheets, verified with the case report forms and analyzed. Results VL has been reported in Nepal since 1980, but CL was reported very recently. From 2016 to 2019, 42 CL cases were reported from 26 different hospitals to EDCD which had been diagnosed on the basis of clinical presentation, and laboratory findings (demonstration of amastigotes in Giemsa-stained smears and rK39 test results). Majority of the patients (31.0%, 13/42) visited to the hospital within 1–6 months of onset of lesions. Facial region (38.1%, 16/42) was the common place where lesions were found ompared to other exposed parts of the body. CL was successfully treated with miltefosine for 28 days. The majority of CL patients did not have history of travel outside the endemic areas and there was no report of sandfly from these areas. Conclusion These evidences highlight that the Government of Nepal need to pay more efforts on CL and include it in differential diagnosis by clinicians, and plan for an active surveillance when the country is targeting leishmaniasis elimination by the year 2025 with the decreasing number of VL cases.

Abstract Background Understanding and improving the durability of long-lasting insecticidal nets (LLINs) in the field are critical for planning future implementation strategies including behavioral change for care and maintenance. LLIN distribution at high coverage is considered to be one of the adjunctive transmission reduction strategies in Nepal’s Malaria Strategic Plan 2014–2025. The main objective of this study was to assess the durability through assessment of community usage, physical integrity, residual bio-efficacy, and chemical retention in LLINs: Interceptor®, Yorkool®, and PermaNet ®2.0 which were used in Nepal during 2009 through 2013. Methods Assessments were conducted on random samples (n = 440) of LLINs from the eleven districts representing four ecological zones: Terai plain region (Kailali and Kanchanpur districts), outer Terai fluvial ecosystem (Surkhet, Dang, and Rupandhei districts), inner Terai forest ecosystem (Mahhothari, Dhanusa, and Illam districts), and Hills and river valley (Kavrepalanchock and Sindhupalchok districts). For each LLIN, fabric integrity in terms of proportionate hole index (pHI) and residual bio-efficacy were assessed. However, for chemical retention, a representative sample of 44 nets (15 Yorkool®, 10 Permanet®2.0, and 19 Interceptor®) was evaluated. Data were analyzed using descriptive statistics stratified by LLINs brand, districts, and duration of exposure. Results On average, duration of use of LLINs was shortest for the Yorkool® samples, followed by PermaNet® 2.0 and Interceptor® with median ages of 8.9 (IQR = 0.4), 23.8 (IQR = 3.2), and 50.1 (IQR = 3.2) months, respectively. Over 80% of field distributed Yorkool® and PermaNet® 2.0 nets were in good condition (pHI< 25) compared to Interceptor® (66%). Bio-efficacy analysis showed that average mortality rates of Interceptor and Yorkool were below World Health Organization (WHO) optimal effectiveness of ≥ 80% compared to 2-year-old PermaNet 2.0 which attained 80%. Chemical retention analysis was consistent with bio-efficacy results. Conclusion This study shows that distribution of LLINs is effective for malaria control; however, serviceable life of LLINs should be considered in terms of waning residual bio-efficacy that warrants replacement. As an adjunctive malaria control tool, National Malaria Control Program of Nepal can benefit by renewing the distribution of LLINs in an appropriate time frame in addition to utilizing durable and effective LLINs.

Abstract Background A significant reduction in malaria cases over the recent years in Nepal has encouraged the government to adopt a goal of “malaria-free nation by 2025.” Nevertheless, to achieve this goal, it is critical to identify the epidemiological burden of malaria by specific regions and areas for an effective targeted intervention. The main objective of this study was to estimate the risk of malaria at Village Development Committee (VDC) level in Nepal based on disease, vector, parasite, and geography. Methods In 2012, the micro-stratification of malaria risk was carried out in 75 districts of Nepal. Instruments such as a questionnaire, case record forms, and guidelines for malaria micro-stratification were developed and pre-tested for necessary adaptations. Village Development Committee (VDC)-wise malaria data were analyzed using exploratory statistics and were stratified by geographical variables that contributed to the risk of malaria. To understand the transmission risk at VDC level, overlay analysis was done using ArcGIS 10. To ensure transparent, reproducible, and comprehensible risk assessment, standard scoring method was selected and utilized for data from 2009 to 2011. Thus identified, three major variables (key determinants) were given weights (wt.) accordingly to stratification of the malaria risk (disease burden, “0.3” wt.; ecology/vector transmission, “0.5” wt.; and vulnerability-population movement, “0.2” wt.). Malaria risk in a VDC was determined based on the overall scores and classified into four categories: no risk, low risk, moderate risk, and high risk. Results Analyzing the overall risk based on scoring of the total VDCs (n = 3976), 54 (1.36%), 201 (5.06%), 999 (25.13%), and 2718 (68.36%) were identified as high-, moderate-, low-, and no-risk categories for malaria, respectively. Based on the population statistics, 3.62%, 9.79%, 34.52%, and 52.05% of the country’s total population live in high-risk, moderate-risk, low-risk, and no-risk VDCs for malaria, respectively. Our micro-stratification study estimates are 100,000 population at high risk. Regional distribution showed that the majority of the high-risk VDCs were identified in the Far- and Mid-western regions (19 and 18 VDCs) followed by Central and Western regions (10 and 7 VDCs) with no high-risk VDCs in the Eastern region. Similarly, 77, 59, 27, 24, and 14 VDCs of the Central, Mid-western, Western, Eastern, and Far-western regions, respectively, were found under moderate malaria risk. Of the low-risk VDCs, 353, 215, 191, 148, and 92 were respectively from the Central, Eastern, Western, Far-western, and Mid-western regions. Conclusions The current micro-stratification study provides insights on malaria risk up to the VDC level. This will help the malaria elimination program to target interventions at the local level thereby ensuring the best utilization of available resources to substantially narrowed-down target areas. With further updates and refinement, the micro-stratification approach can be employed to identify the risk areas up to smaller units within the VDCs (ward and villages).