Distribution of and associated factors for dengue burden in the state of Odisha, India during 2010-2016

Dengue infections in India: A meta-analysis

The escalating impact of dengue infection on health and mortality is a critical global issue. Therefore, it is of interest to assess the current trends of dengue infection in India. We searched through a wide range of internet databases to gather comprehensive studies on the incidence, prevalence, sero-prevalence, cost effectiveness and mortality rate of dengue infection in India from 2014 to 2023 (10 years) in a total of 127 studies. Analysis shows significant heterogeneity (diversity) in reported outcomes (p-values < 0.001). Thus, public health strategies should include early detection of dengue infection in our country.

Global burden and socioeconomic impact of knee osteoarthritis: a comprehensive analysis

Objective

To report the trend changes of the prevalence, incidence, and disability-adjusted life years (DALYs) of knee osteoarthritis (KOA) according to age, sex, sociodemographic index (SDI), and income.

Methods

This analysis used estimates from the broader Global Burden of Disease (GBD) study 2019, which covered 201 countries from 1990 to 2019. National prevalence, incidence, and DALYs were shown by using ggplot2 and maps packages. Five-year intervals were used for age groupings. The Commonwealth and the World Bank income classifications were used for income grouping.

Results

Globally, there were ~364.58 million prevalent cases (females: 225.16 million), 29.51 million incident cases (females: 17.53 million), and 11.53 million DALYs (females: 7.09 million) due to KOA in 2019. The Western Pacific Region had a high endemicity of ~7,319.87 cases per 100,000 people (7.64%). Japan's prevalence rate (12,610.12 cases per 100,000 population) was 10 times that of Somalia (1,178.23) in 2019. In 200 countries (except the United Arab Emirates), the prevalence, incidence, and DALY rates of KOA in 2019 were higher among females than among males and increased with age up to the oldest age group. The prevalence was highest in the high-middle SDI countries, and the incidence and DALYs were highest in the middle SDI countries.

Conclusion

There was a large burden of KOA worldwide, with some notable intercountry variation. Some countries had 10 times the burden of other countries. Increasing population awareness regarding the prevalence, incidence, and DALYs of KOA with a focus on the population in the Western Pacific Region is needed, particularly for older females. informs health policy development, and contributes to improving the efficiency, equity, and effectiveness of healthcare systems.

Mapping the distribution and trends of co-circulating dengue virus serotypes in Odisha, India: A retrospective facility-based analysis

Background Dengue, caused by mosquito bite, is an emerging disease of international concern. Evidence regarding the prevalent dengue serotypes is scarce, but essential for its management during the outbreaks. Hence, we mapped the distribution and trends of currently prevalent dengue virus (DENV) serotypes in Odisha. Methods We conducted a facility-based retrospective study from referral samples sent for the diagnosis/confirmation of dengue in 2018. The samples were serologically tested for enzyme-linked immunosorbent assay (ELISA) IgM antibody and NS1. Only NS1-positive samples were chosen for sero-typing. A pool of 8-10 NS1-positive samples were analysed for district-wise serotypes. Ribonucleic acid extraction and nested polymerase chain reaction (PCR) was done from NS1-positive samples. The PCR products were then subjected to gel electrophoresis. Results A total of 2892 samples were screened for dengue virus across various districts of Odisha where 763 samples were found to be NS1-positive. Thirteen of 18 districts covering all topographies of Odisha predominantly had DENV2 serotype. Only few districts such as Balangir, Kalahandi and Rayagada had mixed serotypes. Conclusion Although DENV2 is predominantly prevalent, mixed serotypes too exist in Odisha. Evidence based on variations of dengue serotypes across topographies, seasons, gender and age groups may support public health efforts in preventing the disease.

Trends and Spatial Pattern Analysis of Dengue Cases in Northeast Malaysia

OBJECTIVES

Dengue remains hyperendemic in Malaysia despite extensive vector control activities. With dynamic changes in land use, urbanisation and population movement, periodic updates on dengue transmission patterns are crucial to ensure the implementation of effective control strategies. We sought to assess shifts in the trends and spatial patterns of dengue in Kelantan, a north-eastern state of Malaysia (5°15'N 102°0'E).

METHODS

This study incorporated data from the national dengue monitoring system (eDengue system). Confirmed dengue cases registered in Kelantan with disease onset between January 1, 2016 and December 31, 2018 were included in the study. Yearly changes in dengue incidence were mapped by using ArcGIS. Hotspot analysis was performed using Getis-Ord Gi to track changes in the trends of dengue spatial clustering.

RESULTS

A total of 10 645 dengue cases were recorded in Kelantan between 2016 and 2018, with an average of 10 dengue cases reported daily (standard deviation, 11.02). Areas with persistently high dengue incidence were seen mainly in the coastal region for the 3-year period. However, the hotspots shifted over time with a gradual dispersion of hotspots to their adjacent districts.

CONCLUSIONS

A notable shift in the spatial patterns of dengue was observed. We were able to glimpse the shift of dengue from an urban to peri-urban disease with the possible effect of a state-wide population movement that affects dengue transmission.

Spatiotemporal epidemiology and forecasting of dengue in the state of Punjab, India: Study protocol

Dengue burden in India is a major public health problem. The present study has been designed to understand mechanisms by which routine data generate evidence. Secondary data analysis of routine datasets to understand spatiotemporal epidemiology and forecast dengue will be conducted. Data science approach will be adopted to generate a reproducible framework in the R environment. The lab-confirmed dengue reported by the state health authorities from 01 January 2015 to 31 December 2019 will be included. Multiple climatic variables from satellite imagery, climatic models, vegetation and built-up indices, and sociodemographic variables will be explored as risk factors. Exploratory data analysis followed by statistical analysis and machine learning will be performed. Data analysis will include geospatial information analysis, time series analysis, and spatiotemporal analysis. The study will provide value addition to the existing disease surveillance mechanisms by developing a framework for incorporating multiple routine data sources available in the country.

Viral characteristics and clinical presentation in dengue co-infection- Findings from a facility based observational study in Odisha, India

Background:

Dengue has affected many countries globally. Two-fifths part of the world is at risk, which can be affected by dengue disease. In India, the dengue incidence has increased in the recent past and emerged as an important health problem in many states including Odisha. Dengue disease presents with atypical clinical symptoms when associated with other co-infections.

Materials and Methods:

A facility-based longitudinal study was carried out over a period of 1 year to determine the dengue co-infection and its outcome. The suspected cases were clinically assessed following a standard case report format and serological investigations including serotyping were carried out.

Results:

33.6% samples were dengue positive of which 78.5% were positive for NS1 Ag, 26.6% positive for dengue IgM and 5.1% to both. Among the dengue positive cases, 60.9% were male and mean age was 31.52 (±17.03) years. High occurrence of cases was during May to November with maximum in August. Among the 975 dengue positives, 57 (5.8%) were found to have co-infection. Chikungunya was the most common co-infection in 71.9%, followed by herpes simplex (HSV) (7%) and other diseases. Fever was the most common presenting symptom (98.2%), followed by myalgia (91.2%), retro orbital pain (91.2%), pain abdomen (12.3%), rash/lesion (8.8%), burning micturition (5.3%), petechiae (1.7%) and pruritus (1.7%) among the co-infected cases.

Conclusions:

All the four dengue serotypes were found to be circulating with DEN 2 as the most predominant one. About 5.8% of dengue cases have co-infection (mainly with Chikungunya) and clinically present with atypical signs and symptoms.

Epidemiology and challenges of dengue surveillance in the WHO South-East Asia Region

Dengue poses a significant health and economic burden in the WHO South-East Asia Region. Approaches for control need to be aligned with current knowledge on the epidemiology of dengue in the region. Such knowledge will ensure improved targeting of interventions to reduce dengue incidence and its socioeconomic impact. This review was undertaken to describe the contemporary epidemiology of dengue and critically analyse the existing surveillance strategies in the region. Over recent decades, dengue incidence has continued to increase with geographical expansion. The region has now become hyper-endemic for multiple dengue virus serotypes/genotypes. Every epidemic cycle was associated with a change of predominant serotype/genotype and this was often associated with severe disease with intense transmission. Classical larval indices are widely used in vector surveillance and adult mosquito samplings are not implemented as a part of routine surveillance. Further, there is a lack of integration of entomological and disease surveillance systems, often leading to inaction or delays in dengue prevention and control. Disease surveillance does not capture all cases, resulting in under-reporting, and has thus failed to adequately represent the true burden of disease in the region. Possible solutions include incorporating adult mosquito sampling into routine vector surveillance, the establishment of laboratory-based sentinel surveillance, integrated vector and dengue disease surveillance and climate-based early warning systems using available technologies like mobile apps.

Forest Coverage and Socioeconomic Factors Associated with Dengue in El Salvador, 2011-2013

Dengue virus serotypes 1, 2, 3, and 4 are transmitted by Aedes aegypti and Aedes albopictus mosquitoes, which cause illness in an estimated 100 million annually. Although dengue viruses are endemic throughout El Salvador, very little is known about their ecology and epidemiology. The principal methods to prevent and reduce dengue cases are through vector control and by adoption of a vaccine. In addition, understanding the environmental and socioeconomic factors associated with dengue could contribute to case reduction by targeting prevention efforts in dengue hotspots. This study investigated environmental and socioeconomic factors associated with dengue cases in El Salvador. Dengue cases were obtained from 2011 to 2013 for 262 municipalities. The mean incidence was determined for each municipality for the 3 year period. Negative binomial regression models evaluated the relationship between dengue cases and the environmental factors elevation, forest coverage, mean annual temperature, and cumulative precipitation. Twelve socioeconomic and infrastructure variables and their relationship with dengue were also investigated by using negative binomial regression. A total of 29,764 confirmed dengue cases were reported. The mean dengue incidence for 2011-2013 was 135/100,000. The highest number of dengue cases occurred in San Salvador and surrounding municipalities, as well as in two additional cities, Santa Ana and San Miguel; the highest incidence of dengue cases (per 100,000) occurred in cities in the west and at the center of the country. Significant environmental variables associated with dengue included temperature, precipitation, and non-forested area. The socioeconomic variables poverty rate, illiteracy rate, and school attendance, and the infrastructure variables percent of homes with sanitary service, municipal trash service, electricity, and cement brick flooring, as well as population density, were also significant predictors of dengue. Understanding these environmental and socioeconomic factors and their relationship with dengue will help design and implement timely prevention strategies and vector control to reduce dengue in El Salvador.

Epidemiology of viral disease outbreaks in Odisha, India (2010-2019)

Despite consistent public health efforts, the burden of viral disease in India remains high. The present study was undertaken to understand the aetiology, frequency and distribution of viral disease outbreaks in the state of Odisha between 2010 and 2019. This was a prospective study conducted at the Virology Research and Diagnostic Laboratory located at ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, wherein all the outbreaks of viral aetiologies were investigated and analysed to provide a comprehensive picture of the state of viral disease outbreaks in the region. A total of 191 suspected viral outbreaks were investigated by the team from VRDL during September 2010 and September 2019 reported from all the 30 districts of Odisha. Annual number of suspected cases ranged from 185 to 1002. The most commonly suspected outbreaks were of viral hepatitis (55 outbreaks; 1223 cases) followed by dengue (45 outbreaks; 1185 cases), chickenpox (30 outbreaks; 421 cases), viral encephalitis (27 outbreaks; 930 cases), measles (23 outbreaks; 464 cases), chikungunya (10 outbreaks; 593 cases) and rubella (1 outbreak; 60). The outbreaks peaked in frequency and intensity during the months of July and September. The epidemiology of viral disease outbreaks in the region is presented in the study. Health system preparedness based on evidence is essential for early detection and adequate response to such viral outbreaks.

Effects of natural and socioeconomic factors on dengue transmission in two cities of China from 2006 to 2017

Dengue fever (DF) is a common and rapidly spreading vector-borne viral disease in tropical and subtropical regions. In recent years, in China, DF still poses an increasing threat to public health in many cities; but the incidence shows significant spatiotemporal differences. The purpose of this study was to identify the key factors affecting the spatial and temporal distribution of DF. We collected natural environmental and socio-economic data for two adjacent cities, Guangzhou (73 variables) and Foshan (71 variables), with the most DF cases in China. We performed random forest modelling to rank the factors according to their level of importance, and used negative binomial regression analysis to compare the risk factors between outbreak years and non-outbreak years. The natural environmental factors contributing to DF incidence for Guangzhou were temperature (relative risk (RR) = 18.80, 95% confidence interval (CI) = 3.11-113.67), humidity (RR = 1.85, 95% CI = 1.17-2.90) and green area (RR = 12.11, 95% CI = 6.14-55.50), and for Foshan was forest coverage (RR = 5.83, 95% CI = 2.72-12.45). Socio-economic impact were shown in Guangzhou with foreign visitor (RR = 1.18, 95% CI = 1.05-1.34) and oversea air passenger transport (RR = 7.34, 95% CI = 2.26-23.86); in Foshan, with oversea tourism (RR = 1.65, 95% CI = 1.34-2.04); and in Guangzhou-Foshan, with the development of intercity metro (RR = 1.26, 95% CI = 1.10-1.44). The difference between the two cities was the greater impact of the foreign visitor, green spaces and climate factor on DF in Guangzhou; the impact of the construction of intercity metro; and the more significant impact of oversea tourism on DF in Foshan. Our results suggest meaningful clues to public health authorities implementing joint interventions on DF prevention and early warning, to increase health education on DF prevention for international visitors and oversea travelers, and cross-city metro passengers; using rapid body temperature detection in public places such as airports, metros and parks can help detect cases early.

Risk factors for dengue outbreaks in Odisha, India: A case-control study

BACKGROUND

Environmental and climatic risk factors of dengue outbreak has been studied in detail. However, the socio-epidemiological association with the disease is least explored. The study aims to identify the social and ecological factors associated with emerging dengue in Odisha, India.

METHODS

A population-based case-control study (age and sex matched at the ratio of 1:1) was conducted in six districts of the state in 2017. A structured validated questionnaire was used to collect information for each consenting participant. An ecological household survey was done using a checklist during the month of July-September. Along with the descriptive statistics, conditional logistic regression model was used to calculate the adjusted odds ratio using STATA.

RESULTS

Of 380 cases, nearly 55% were male and the median age was 33years. The adjusted odds of having dengue was nearly three times higher among the people having occupation which demands long travel, presence of breeding sites (1.7; 95% CI 1.2-2.6), presence of swampy area near home (1.5; 95% CI 1.1-2.1) and having travel history close to the index date (1.6; 95% CI 1.1-2.4). People staying in thatched houses had three times higher risk of the disease, however, households keeping the swampy areas clean had 50% less risk for the disease (0.5; 95% CI 0.31-0.67). Nearly 22.2% of cases had a travel history during the index date. Of them, 36% had diagnosis before the travel, whereas, 64% developed the disease after the returning from the travel.

CONCLUSION

Household factors such as occupation and ecological condition of households play important roles in dengue outbreaks in Odisha. However, our study suggests travel/commuting are also essential factors to be considered during disease prevention planning.