14 research outputs found
Detection of Anti- Leptospira
Leptospirosis is a globally distributed zoonosis with varied clinical outcomes and multiorgan involvement in humans. In this study conducted from July 2011 to December 2011, 178 serum samples from patients suspected of leptospirosis were tested by Panbio IgM ELISA at National Public Health Laboratory, Kathmandu, out of which 51 (28.65%) were positive for anti-Leptospira IgM antibody. Leptospirosis was more common in people in their 2nd and 3rd decades of their life which together comprised 56.86% of the total positive cases. Most of those tested positive were farmers followed by students and housewives. Both animal contact and water contact seemed to play significant roles in disease transmission. Symptoms were vague with the most common being fever, headache, myalgia, abdominal pain, vomiting, jaundice, and diarrhoea. Life style heavily dominated by agronomical and farming activities in Nepal is conducive to leptospirosis transmission. Leptospirosis seems to be a significant public health problem in Nepal but is underestimated. In resource poor countries like Nepal where laboratories performing MAT or maintaining cultures are rarely available, serological test like ELISA could well depict the scenario of the disease prevalence
Outbreak of pandemic influenza A/H1N1 2009 in Nepal
<p>Abstract</p> <p>Background</p> <p>The 2009 flu pandemic is a global outbreak of a new strain of H1N1 influenza virus. Pandemic influenza A (H1N1) 2009 has posed a serious public health challenge world-wide. Nepal has started Laboratory diagnosis of Pandemic influenza A/H1N1 from mid June 2009 though active screening of febrile travellers with respiratory symptoms was started from April 27, 2009.</p> <p>Results</p> <p>Out of 609 collected samples, 302 (49.6%) were Universal Influenza A positive. Among the influenza A positive samples, 172(28.3%) were positive for Pandemic influenza A/H1N1 and 130 (21.3%) were Seasonal influenza A. Most of the pandemic cases (53%) were found among young people with ≤ 20 years. Case Fatality Ratio for Pandemic influenza A/H1N1 in Nepal was 1.74%. Upon Molecular characterization, all the isolated pandemic influenza A/H1N1 2009 virus found in Nepal were antigenically and genetically related to the novel influenza A/CALIFORNIA/07/2009-LIKE (H1N1)v type.</p> <p>Conclusion</p> <p>The Pandemic 2009 influenza virus found in Nepal were antigenically and genetically related to the novel A/CALIFORNIA/07/2009-LIKE (H1N1)v type.</p
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
Influenza virus types and subtypes among pediatric patients having influenza like illness in summer season
Background: Acute respiratory infections (ARIs) represent one of the major causes of childhood mortality and morbidity in Nepal. The Influenza virus is one of the common causes of viral ARIs and bacterial infection secondary to influenza contributes to majority of childhood death worldwide. However, the diagnosis of influenza virus infection is not routinely suggested in Nepal even for children clinically presenting with influenza like illness (ILI). Methods: With an aim to describe the status of viral influenza in Nepalese children with ILI, a throat swab and a nasal swab specimen were collected from each pediatric ILI patients visiting to the outpatient department of Kanti Children's Hospital (KCH). Viral influenza was diagnosed by rapid antigen detection test and further confirmed by reverse transcription-polymerase chain reaction (RT-PCR). Results: Among 200 ILI cases analyzed, 20 (10.0%) cases were confirmed as influenza A and 5 (2.5%) were confirmed as influenza B by rapid antigen detection test. Among 20 influenza A cases diagnosed by rapid test, 16 (80.0 %) were confirmed as A/H3 type and one was identified as pdm H1N109 by RT-PCR. Similarly, 3 out of 5 influenza B positive cases in rapid test were confirmed as influenza B by RT-PCR. Conclusion: Though, our study does not represent whole year data, this finding suggests routine influenza testing of all pediatric ILI cases
Profile of the 2016 dengue outbreak in Nepal
Abstract Objective The objective of this study was to obtain clinical, virological and demographic data detailing the 2016 dengue outbreak in Nepal. Results Dengue disease was first reported in Nepal in 2004 and several major outbreaks have occurred since then, with a significant impact on public health. An outbreak of dengue fever occurred in Nepal during June to November 2016, with a peak number of cases reported in September. 1473 patients with laboratory confirmed DENV infections visited or were admitted to hospitals during this period. The most common clinical symptoms included fever, headache, joint pain and thrombocytopenia. Serotyping of 75 serum samples from patients having fever for less than 4 days was carried out with a dengue virus (DENV) serotype-specific RT-PCR strategy. Our results indicate that the dengue outbreak in Nepal during 2016 was caused predominantly, if not exclusively, by DENV-1, representing a shift in the prevailing serotype from DENV-2, the dominant serotype characterizing the 2013 dengue epidemic in Nepal. Hopefully, this report will assist Nepalese public health agencies in developing improved dengue-related programs including mosquito-vector control, DENV surveillance, and diagnosis and treatment of dengue fever patients, in order to reduce the impact of future dengue epidemics
Etiology of Coinfections in Children with Influenza during 2015/16 Winter Season in Nepal
Acute respiratory infections (ARIs) are one of the major public health problems in developing countries like Nepal. Besides the influenza, several other pathogens are responsible for acute respiratory infection in children. Etiology of infections is poorly characterized at the course of clinical management, and hence empirical antimicrobial agents are used. The objective of this study was to characterize the influenza and other respiratory pathogens by real-time PCR assay. A total of 175 throat swab specimens of influenza-positive cases collected at National Influenza Center, Nepal, during the 2015/16 winter season were selected for detecting other respiratory copathogens. Total nucleic acid was extracted using Pure Link viral RNA/DNA mini kit (Invitrogen), and multiplex RT-PCR assays were performed. Influenza A and B viruses were found in 120 (68.6%) and 55 (31.4%) specimens, respectively, among which coinfections were found in 106 (60.6%) specimens. Among the influenza A-positive cases, 25 (20.8%) were A/H1N1 pdm09 and 95 (79.2%) were A/H3 subtypes. Viruses coinfected frequently with influenza virus in children were rhinovirus (26; 14.8%), respiratory syncytial virus A/B (19; 10.8%), adenovirus (14; 8.0%), coronavirus (CoV)-HKU1 (14; 8.0%), CoV-OC43 (5; 2.9%), CoV-229E (2; 1.1%), metapneumovirus A/B (5; 2.9%), bocavirus (6; 3.4%), enterovirus (5; 2.9%), parainfluenza virus-1 (3; 1.7%), and parainfluenza virus-3 (2; 1.1%). Coinfection of Mycoplasma pneumoniae with influenza virus was found in children (5; 2.8%). Most of the viral infection occurred in young children below 5 years of age. In addition to influenza virus, nine different respiratory pathogens were detected, of which coinfections of rhinovirus and respiratory syncytial virus A/B were predominantly found in children. This study gives us better information on the respiratory pathogen profile and coinfection combinations which are important for diagnosis and treatment of ARIs
Etiology of Coinfections in Children with Influenza during 2015/16 Winter Season in Nepal
Burden of human metapneumovirus infections among children with acute respiratory tract infections attending a Tertiary Care Hospital, Kathmandu
Abstract Background Acute respiratory infections (ARIs) are one of the most common causes of mortality and morbidity worldwide. Every year millions of children suffer from viral respiratory tract infections (RTIs) ranging from mild to severe illnesses. Human Metapneumovirus (HMPV) is among the most frequent viruses responsible for RTIs. However, HMPV infections and their severity among children have not been explored yet in Nepal. Purpose Therefore, the study was focused on HMPV infections and other potential viral etiologies or co-infections using multiplex PCR among children attending Kanti Children’s Hospital and assessed the clinical characteristics of the infections as well as found the co-infections. A hospital-based cross-sectional study was designed and a convenience sampling method was used to enroll children of less than 15 years with flu-like symptoms from both outpatients and inpatients departments over three months of the study period. Results HMPV infection (13.3%) was the most predominant infection among the different viral infections in children with ARIs in Kanti Children’s Hospital. The HMPV was more prevalent in the age group less than three years (21.8%). Cough and fever were the most common clinical features present in all children infected with HMPV followed by rhinorrhea, sore throat, and wheezing. HMPV-positive children were diagnosed with pneumonia (42.9%), bronchiolitis (28.5%), upper respiratory tract infections (14.3%), and asthma (14.3%). The prevalence of HMPV was high in late winter (14.3%) followed by early spring (13.5%). Conclusions This study provides the baseline information on HMPV and associated co-infection with other respiratory viruses for the differential diagnosis based on molecular methods and also the comparison of clinical presentations among the different respiratory syndromes