Integrated Disease Surveillance Programme Research Articles

Epidemiological Trends of Dengue in One of the Western Hilly Areas of Himachal Pradesh.

Dengue is one of the neglected tropical diseases, with a wide spectrum of diseases, ranging from acute febrile illness dengue fever to life-threatening dengue hemorrhagic fever or dengue shock syndrome. In recent years, it has become a major public health concern in many nonendemic areas as well. A secondary data analysis of records available with district Integrated Disease Surveillance Programme cell was conducted to study distribution (time, place, and person) of dengue from 2017 to 2022 in Kangra, a sub-Himalayan district of Himachal Pradesh (HP). In the evaluated period (2017-2022), a total of 6008 cases suspected of dengue were tested and test positivity of 7% (441) with male gender predominance was found. Mean age of the diagnosed cases was 37.7 ± 16.8 years. A seasonal trend was observed starting from late August to November in all study years. Dengue is still a neglected disease, but it has shown its presence especially in this part of HP, indicating the need for better preparation and sensitization of vector-borne disease control program activities, especially in post-monsoon, to prevent future epidemics.

IJCM_369A: Notification of malaria and dengue outbreaks during COVID-19 pandemic: A secondary analysis of weekly IDSP reporting

Background: Like many other diseases, vector borne diseases related health activities got affected during COVID-19 due to disruption in health services. The preventive measures, vector surveillance, diagnostics, early diagnosis, and management are likely to have been affected. Objective: To explore the vector-borne disease trends as outbreaks from January 2021 to December 2023 using weekly reports of Integrated Disease Surveillance Programme (IDSP). Methodology: We used the secondary data of the weekly reports of IDSP weekly reports from Jan 2020 Dec 2023. We included dengue and malaria as two important diseases to represent the prevailing vector borne diseases in the country. The outbreak data collected were entered in MS Excel and reported as frequency and proportions to visualize the time trends during the COVID-19 pandemic. Results: The outbreaks of malaria were found to occur mainly in the second half of the year with 63% and 80% outbreaks in the years 2020 and 2021 respectively, coinciding with the onset of monsoons. Maximum number of outbreaks was reported in the year of 2021, followed by 2022 with number of outbreaks being 20 and 19 respectively. Maximum number of dengue outbreaks were reported in the year 2021 followed by year 2022 with the numbers being 114 and 81 respectively. The year 2020 had around half the number of outbreaks as of the year 2022 (42 outbreaks). The first half of the year 2023 reported 25 outbreaks. Conclusion: Both malaria and dengue had maximum number of outbreaks in the year 2021 followed by a slight dip in the year 2022. At the onset of pandemic, the number of outbreaks were quite less compared to the subsequent years, probably due to the lockdown imposed.

IJCM_305A: Forecasting Dengue and Chikungunya incidence using Time Series Analysis Modelling

Background: In recent years, the rise in vector-borne diseases, particularly Dengue and Chikungunya, has posed a significant public health challenge globally. Epidemiological data from the Integrated Disease Surveillance Program (IDSP) is a useful resource for forecasting and early outbreak identification by applying effective models like Sessional Autoregressive Integrated Moving Average (SARIMA) models has proven effective in capturing temporal dependencies in various fields. Objective: To forecast the dengue and chikungunya cases in India using Seasonal Autoregressive Integrated Moving Average models. Methodology: we preprocessing the IDSP dataset to extract relevant temporal patterns and trends. Subsequently, SARIMA models are applied to capture the time dependent dynamics of disease occurrences. The model’s performance is evaluated through rigorous validation processes, including cross-validation techniques, to ensure its reliability and generalizability. Results: This study considered a secondary data set of weekly dengue and chikungunya cases over the period of 2019 to 2023. The time plot shows several spikes in the data, indicating periods where the number of dengue cases increased significantly in the most recent years. Forecast of the future dengue and chikungunya cases was done for the next one year (2024). we observed that the number of dengue and chikungunya cases has fluctuated over time but has generally remained within a certain range. The forecast predicts a significant increase in cases as we move towards the latter half of 2024, with a very sharp spike towards the end of the forecast period. Conclusion: In conclusion, utilizing a secondary dataset spanning from 2019 to 2023, this study employed time series analysis to forecast future Dengue and Chikungunya cases. The forecast predicts a significant increase in dengue cases during 2024 which can lead to potential implications for public health practitioners, policymakers, and researchers involved in infectious disease management.

Mapping the stability of febrile illness hotspots in Punjab from 2012 to 2019- a spatial clustering and regression analysis

IntroductionFebrile illnesses (FI) represent a typical spectrum of diseases in low-resource settings, either in isolation or with other common symptoms. They contribute substantially to morbidity and mortality in India. The primary objective was to study the burden of FI based on Integrated Disease Surveillance Programme (IDSP) data in Punjab, analyze geospatial and temporal trends and patterns, and identify the potential hotspots for effective intervention.MethodsA retrospective ecological study used the district-level IDSP reports between 2012 and 2019. Diseases responsible for FI on a large scale, like Dengue, Chikungunya, Malaria (Plasmodium Falciparum, P. Vivax), Enteric fever, and Pyrexia of Unknown Origin (PUO), were included in the analysis. The digital map of Punjab was obtained from GitHub. Spatial autocorrelation and cluster analysis were done using Moran’s I and Getis-Ord G* to determine hotspots of FI using the incidence and crude disease numbers reported under IDSP. Further, negative binomial regression was used to determine the association between Spatio-temporal and population variables per the census 2011. Stable hotspots were depicted using heat maps generated from district-wise yearly data.ResultsPUO was the highest reported FI. We observed a rising trend in the incidence of Dengue, Chikungunya, and Enteric fever, which depicted occasional spikes during the study period. FI expressed significant inter-district variations and clustering during the start of the study period, with more dispersion in the latter part of the study period. P.Vivax malaria depicted stable hotspots in southern districts of Punjab. In contrast, P. Falciparum malaria, Chikungunya, and PUO expressed no spatial patterns. Enteric Fever incidence was high in central and northeastern districts but depicted no stable spatial patterns. Certain districts were common incidence hotspots for multiple diseases. The number of cases in each district has shown over-dispersion for each disease and has little dependence on population, gender, or residence as per regression analysis.ConclusionsThe study demonstrates that information obtained through IDSP can describe the spatial epidemiology of FI at crude spatial scales and drive concerted efforts against FI by identifying actionable points.

Overview of web-based public health surveillance system in Uttarakhand: Integrated health information platform under integrated disease surveillance programme

Overview of web-based public health surveillance system in Uttarakhand: Integrated health information platform under integrated disease surveillance programme - IJFCM- Print ISSN No: - 2394-6768 Online ISSN No:- 2394-6776 Article DOI No:- 10.18231/j.ijfcm.2023.001, Indian Journal of Forensic and Community Medicine-Indi

Evaluation of Scrub Typhus Surveillance, Alwar District, Rajasthan, India, July-August 2020.

Scrub typhus is one of the most underreported and fatal illnesses accounting for 23% of all febrile illness. Rajasthan reported cases during 2018-2019 in state reporting system but did not report any case to central Integrated Disease Surveillance Programme (IDSP) unit. We evaluated the Scrub typhus surveillance system in Alwar district, Rajasthan, with the objective of describing and evaluating the system and providing evidence-based recommendations to identify gaps. In cross-sectional study, we reviewed records and conducted key informant interviews at district- and block-level health facilities. Using US Centers for Disease Control guidelines, we evaluated the system by framing indicators for selected attributes for a defined reference period. Overall performance was ranked as outstanding (90-100%), excellent (80-89%), very good (70-79%), good (60-69%), and poor (<60%). Line list of confirmed cases was sent from district to block level for additional active case search (ACS) to implement control measures. We conducted 26 key informant interviews and reviewed records and calculated simplicity as 79%, flexibility 100%, data quality 46%, acceptability 92%, representativeness 48%, timeliness 43%, and stability 79%. Epidemiological surveillance (active and passive) is a core intervention under scrub typhus surveillance system. Lab reports were incompletely uploaded on IDSP portal. Surveillance reports should be updated after each ACS. Reporting format under IDSP should be uploaded timely, and lab reports from state should be sent within 48 hours of diagnosis so that case investigation is not delayed.

Ten-year (2013–2022) trends of measles outbreaks reported under the Integrated Disease Surveillance Program in India

Ten-year (2013–2022) trends of measles outbreaks reported under the Integrated Disease Surveillance Program in India

Endemic, emerging and re-emerging zoonotic diseases: The way forward!

Endemic, emerging and re-emerging zoonotic diseases: The way forward!

Trends and seasonality of vector borne diseases in Kerala

Background: Even though epidemiological transition of Kerala is from communicable to non-communicable diseases, re-emerging communicable diseases is a challenge to health service system. Information about disease trends and pattern and seasonal variation is necessary to ensure healthy life. This study aims to find out the trend and pattern in vector borne diseases and its association with seasons.Methods: Study used integrated disease surveillance programme (IDSP) data of vector borne diseases from Directorate of Health Services, Kerala. Seasons are classified as summer, rainy and winter. Mean differences in frequency between two sample proportions (between seasons) were tested using analysis of variance (ANOVA) test.Results: The fluctuations in vector borne disease are mainly due to dengue. Percent share of acute encephalitis syndrome (AES) and Japanese encephalitis (JE) is low but fatality is high among these diseases. Fatality rate for dengue and malaria is low but scrub typhus is high. Thiruvananthapuram is in the first position in reporting these diseases except in 2018, when Malappuram holds the first position. Idukki, Kottayam and Wayanad are the districts with lowest percents. Diseases increase during rainy season.Conclusions: There is necessary monitoring from LSGD and health institutions at primary level to do grass root level sanitation and health awareness to prevent dengue fever. Proper monitoring of entering data from health institutions is needed. The study provides an insight to the vector borne diseases in Kerala which help planning the infrastructure and human resources in public hospitals.

Multimodal surveillance of SARS-CoV-2 at a university enables development of a robust outbreak response framework

BackgroundUniversities are vulnerable to infectious disease outbreaks, making them ideal environments to study transmission dynamics and evaluate mitigation and surveillance measures. Here, we analyze multimodal COVID-19-associated data collected during the 2020-2021 academic year at Colorado Mesa University and introduce a SARS-CoV-2 surveillance and response framework.MethodsWe analyzed epidemiological and sociobehavioral data (demographics, contact tracing, and WiFi-based co-location data) alongside pathogen surveillance data (wastewater and diagnostic testing, and viral genomic sequencing of wastewater and clinical specimens) to characterize outbreak dynamics and inform policy. We applied relative risk, multiple linear regression, and social network assortativity to identify attributes or behaviors associated with contracting SARS-CoV-2. To characterize SARS-CoV-2 transmission, we used viral sequencing, phylogenomic tools, and functional assays.FindingsAthletes, particularly those on high-contact teams, had the highest risk of testing positive. On average, individuals who tested positive had more contacts and longer interaction durations than individuals who never tested positive. The distribution of contacts per individual was overdispersed, though not as overdispersed as the distribution of phylogenomic descendants. Corroboration via technical replicates was essential for identification of wastewater mutations.ConclusionBased on our findings, we formulate a framework that combines tools into an integrated disease surveillance program, which can be implemented in other congregate settings with limited resources.

Dengue risk zone mapping of Thiruvananthapuram district, India: a comparison of the AHP and F-AHP methods.

Dengue fever, which is spread by Aedes mosquitoes, has claimed many lives in Kerala, with the Thiruvananthapuram district bearing the brunt of the toll. This study aims to demarcate the dengue risk zones in Thiruvananthapuram district using the analytical hierarchy process (AHP) and the fuzzy-AHP (F-AHP) methods. For the risk modelling, geo-environmental factors (normalized difference vegetation index, land surface temperature, topographic wetness index, land use/land cover types, elevation, normalized difference built-up index) and demographic factors (household density, population density) have been utilized. The ArcGIS 10.8 and ERDAS Imagine 8.4 software tools have been used to derive the risk zone maps. The area of the risk maps is classified into five zones. The dengue risk zone maps were validated using dengue case data collected from the Integrated Disease Surveillance Programme portal. From the receiver operating characteristic (ROC) curve analysis and the area under the ROC curve (AUC) values, it is proved that the F-AHP method (AUC value of 0.971) has comparatively more prediction capability than the AHP method (AUC value of 0.954) in demarcating the dengue risk zones. Also, based on the comparison of the risk zone map with actual case data, it was confirmed that around 82.87% of the dengue cases occurred in the very high and high-risk zones, thus proving the efficacy of the model. According to the dengue risk map prepared using the F-AHP model, 9.09% of the area of Thiruvananthapuram district is categorized as very high risk. The prepared dengue risk maps will be helpful for decision-makers, staff with the health, and disaster management departments in adopting effective measures to prevent the risks of dengue spread and thereby minimize loss of life.

Cholera Outbreaks in India, 2011-2020: A Systematic Review.

Fecal contamination of water sources and open defecation have been linked to cholera outbreaks in India. However, a systematic review on the drivers responsible for these outbreaks has yet to be published. Here, we systematically review the published literature on cholera outbreaks in India between 2011 and 2020. We searched studies in English in three databases (MEDLINE, EMBASE, and Web of Science) and the Integrated Disease Surveillance Program that tracks cholera outbreaks throughout India. Two authors independently extracted data and assessed the quality of the included studies. Quantitative data on the modes of transmission reviewed in this study were assessed for any change over time between 2011–2015 and 2016–2020. Our search retrieved 10823 records initially, out of which 81 full-text studies were assessed for eligibility. Among these 81 studies, 20 were eligible for inclusion in this review. There were 565 reported outbreaks between 2011 and 2020 that led to 45,759 cases and 263 deaths. Outbreaks occurred throughout the year; however, they exploded with monsoons (June through September). In Tamil Nadu, a typical peak of cholera outbreaks was observed from December to January. Seventy-two percent (33,089/45,759) of outbreak-related cases were reported in five states, namely Maharashtra, West Bengal, Punjab, Karnataka, and Madhya Pradesh. Analysis of these outbreaks highlighted the main drivers of cholera including contaminated drinking water and food, inadequate sanitation and hygiene (including open defecation), and direct contact between households. The comparison between 2011–2015 and 2016–2020 showed a decreasing trend in the outbreaks that arose due to damaged water pipelines. Many Indians still struggle with open defecation, sanitation, and clean water access. These issues should be addressed critically. In addition, it is essential to interrupt cholera short-cycle transmission (mediated by households, stored drinking water and foodstuffs) during an outbreak. As cholera is associated with deprivation, socio-economic development is the only long-term solution.

Geospatial Epidemiology of chicken-pox disease in India between 2015-2021: A GIS based analysis

Introduction: In this paper, we introduce geographical information systems (GIS) as a tool to study trends in disease spread in time and space. Based on data gathered by the integrated disease surveillance programme (IDSP), we can see where outbreaks of Chickenpox have occurred. Objective: The aim of this study is to assess the trends in chickenpox diseases in India between January 2015 and April 2021 using GIS maps. Methods: For the collection of secondary data relating to chickenpox, a free app called collect 5 was used for collecting data weekly from the IDSP website and then storing them in an online server. In this project, variables that needed to be processed with QGIS were combined with table attributes of many shapefiles of India and presented as maps. Results: Between Jan 2015 and May 2021, 1269 chickenpox outbreaks (27,257 cases) have been recorded. Thirty-one deaths have been confirmed, with most occurring in Bihar and Uttar Pradesh. Nineteen states did not report any deaths. According to the seasonally adjusted trend, the number of cases was highest during the months of January and March. Conclusion: In summary, geographic information systems have become an invaluable tool for mapping the hotspots of acute epidemics and planning public health interventions to prevent the spread of these diseases.

India's strategy on surveillance system- A paradigm shift from an Integrated Disease Surveillance Programme (IDSP) to an Integrated Health Information Platform (IHIP)

A well-built, national-level surveillance system for communicable and non-communicable diseases is the hour of need for any country. As part of International Health Regulation (IHR) core capacity building and to strengthen public health surveillance system, India needs a comprehensive information system to monitor emerging public health threats, disasters and mass events. India has identified the need for such a system during the mid-90s and launched the WHO-supported National Surveillance Project for Communicable Diseases (NSPCD) in 1997–98 in selected districts.

Evaluation of point of entry surveillance for COVID-19 at Mumbai international airport, India, July 2020.

India started Point of entry (PoE) surveillance at Mumbai International Airport, screening passengers returning from coronavirus disease (COVID-19)-affected countries using infrared thermometers. We evaluated in July 2020 for March 1-22 with the Centers for Disease Control and Prevention evaluation framework. We conducted key informant interviews, reviewed passenger self-reporting forms (SRFs) (randomly selected) and relevant Airport Health Organization and Integrated Disease Surveillance Programme (IDSP) records. Of screened 165,882 passengers, three suspects were detected and all were reverse transcription-polymerase chain reaction negative. Passengers under-quarantine line-listing not available in paper-based PoE system, eight written complaints: 6/8 SRF filling inconvenience, 3/8 no SRF filling inflight announcements, and standing in long queues for their submission. Outside staff deployed 128/150 (85.3%), and staff: passenger ratio was 1:300. IDSP reported 59 COVID-19 confirmed cases against zero detected at PoE. It was simple, timely, flexible, and useful in providing information to IDSP but missed cases at PoE and had poor stability. We recommended dedicated workforce and data integration with IDSP.

Clinical Features and Predisposing Factors Influencing the Outcome of COVID-19 in First and Second Wave at Nanded, Maharashtra- A Retrospective Study

Introduction: It is crucial to determine possible factors associated with exacerbation of the disease due to the alarming global spread, morbidity and mortality associated with Coronavirus Disease-2019 (COVID-19). It is important to determine the co-morbidities associated with this disease which will help in better treatment of patients in time and to make amendments to management policy. Aim: To compare the clinical features, and predisposing factors (socio-demographic factors and co-morbidities) influencing the outcome in COVID-19 infected patients admitted in a tertiary care centre in the first and second wave of COVID-19 pandemic. Materials and Methods: The retrospective study was conducted at the Department of Microbiology, Dr. Shankarrao Chavan Government Medical College, Nanded, Maharashtra, India. The data was collected from the electronic resource which was maintained by the institute Integrated Disease Surveillance Program (IDSP) health record reporting database for the duration of June 2020 to August 2021. This data included patient’s demographic details (age, sex, address, contact number), other details (history of close contacts, international travel) clinical history, different types of symptoms (ICMR patient category), comorbidities, number of patients requiring ICU admission, type of sample, the outcome in terms of death and discharge, cause of death. The analysis was done for the complete data and then for two separate durations of the first and second wave which were compared later with Chi-square test (Bivariate analysis). Results: A total of 8841 patients were involved and the majority of patients in the study were between the age group of 30-75 years, there was a predominance of males in first and second waves with 6514 (73.7%) and 5795 (58.6%) respectively. The paediatric patients had a mortality rate of 100% (n=7) found in the second wave. Fever (39%) and dyspnea (22%) were found as the commonest presentation in both waves. Gastrointestinal manifestations were observed relatively more in the second wave. The serious patients on ventilator were found to have (&gt;91%) the highest mortality. It appeared that the highest attributable risk to severity and mortality (eight to ten times increased) was due to hypertension, diabetes and other co-morbidities. Pregnancy did not predisposed to be as a risk factor. Conclusion: Prompt management and preventive care are needed for patients with co-morbidities to avoid the exacerbation of COVID-19 as well as drug cross interactions.

Knowledge, Attitudes, and Practices towards COVID-19 Pandemic among Residents of the Jharkhand State, India: An Online Survey

Background: People's adherence to control measures is imperative in the fight against COVID-19. The present study was done to evaluate knowledge, attitudes, and practices towards COVID-19 among residents of Jharkhand and to assist the government in deciding further course of action during the COVID-19 outbreak.&#x0D; Methods: This study was an online cross-sectional survey. The link to the questionnaire was displayed on the official website of Rajendra Institute of Medical Sciences, Ranchi, National Health Mission, Jharkhand, official website of all districts under Jharkhand state administration, Integrated Disease Surveillance Programme and Information &amp; Public Relations department. Participation of residents in the survey was extensively propagated using mass media mainly local television networks, radio channels and newspapers.&#x0D; Results: A total of 4683 responses were received from all districts of Jharkhand. The majority of the participants were young adults (47.5%) and the number of male participants was more than the females (81.4%). The mean correct knowledge score for participants of this study was 10.73+2.2 (maximum attainable score was 14) while the mean practice score for the participants was 4.5+0.69 (maximum attainable score was 5). The knowledge score of the participants was significantly associated with their age, education status and economic class (p&lt;0.0001). The participants largely held an optimistic attitude and healthy practices towards COVID-19. Conclusion: Participants had a positive attitude but were also logically worried and uncertain about the near future. Adequate knowledge of participants was visible in their practices. There was however a gap across age groups, gender, literacy and income levels which should be addressed in future campaigns.

Nipah Virus Disease: Recent Perspective and One Health Approach.

Background:Nipah virus (NiV) first emerged in 1998 in Malaysia, causing an outbreak of respiratory illness and encephalitis in pigs. Pig-to-human transmission of NiV associated with severe febrile encephalitis was described, and it was thought to occur through close contact with infected animals. The first outbreak was reported in India in Siliguri, West Bengal in 2001 followed by Nadia, West Bengal and adjoining areas of Bangladesh in 2007, where an intermediate animal host was not identified, suggesting bat-to-human and human-to-human transmissions. Although it is extremely difficult to document the spillover event and ascertain crossing of trans-natural boundaries by bats and bringing new viruses in an unexposed population, efforts for source identification are important to understand the epidemiology of disease. As the disease transcends beyond one species and has shown to infect humans, it therefore requires the ‘One Health approach’ in which multiple sectors coordinate and work together to achieve better public health outcomes.Objective:We summarize the re-emergence and response of the Nipah virus outbreaks (NiVD) in Kerala, India, about 1800 kms away, a decade later in 2018 and 2019. The paper recapitulates involvement of various stakeholders from the Ministry of Health and Family Welfare, Directorate of Health Research, Indian Council of Agricultural Research, State Health Department, State Animal Husbandry, District Administration, and multidisciplinary response mechanism during the NiVD outbreaks of 2018 and 2019.Methods:Information was collected from the Press Information Bureau (PIB), media/weekly alerts from the Integrated Disease Surveillance Programme (IDSP), news articles from print and electronic media, newsletters, advisories from the National Centre for Disease Control (NCDC), Disease Outbreak News (DON), World Health Organization (WHO), and published papers from various stakeholders.Findings & Conclusion:The evidence of NiV in humans and bats, with samples collected from the outbreak sites, was laboratory confirmed. The multidisciplinary response mechanisms during the 2018 outbreak helped in further understanding the importance of the One Health approach for systemic and streamlined response utilizing existing surveillance systems. This was of utmost help in the subsequent outbreak of the disease that occurred during 2019, wherein there was no documented spread of disease from the index case and no mortality was observed. This success reiterates the need for institutionalizing the involvement and cooperation of various departments and organizations during public health emergencies, especially of Zoonotic diseases, using the One Health approach.

Comparing COVID-19 mortality across selected states in India: The role of age structure

BackgroundMortality rates provide an opportunity to identify and act on the health system intervention for preventing deaths. Hence, it is essential to appreciate the influence of age structure while reporting mortality for a better summary of the magnitude of the epidemic. ObjectivesWe described and compared the pattern of COVID-19 mortality standardized by age between selected states and India from January to November 2020. MethodsWe initially estimated the Indian population for 2020 using the decadal growth rate from the previous census (2011). This was followed by estimations of crude and age-adjusted mortality rate per million for India and the selected states. We used this information to perform indirect-standardization and derive the age-standardized mortality rates for the states for comparison. In addition, we derived a ratio for age-standardized mortality to compare across age groups within the state. We extracted information regarding COVID-19 deaths from the Integrated Disease Surveillance Programme special surveillance portal up to November 16, 2020. ResultsThe crude mortality rate of India stands at 88.9 per million population (118,883/1,337,328,910). Age-adjusted mortality rate (per-million) was highest for Delhi (300.5) and lowest for Kerala (35.9). The age-standardized mortality rate (per million) for India is (<15 years = 1.6, 15–29 years = 6.3, 30–44 years = 35.9, 45–59 years = 198.8, 60–74 years = 571.2, ≥75 years = 931.6). The ratios for age-standardized mortality increase proportionately from 45 to 59 years age group across all the states. ConclusionThere is high COVID-19 mortality not only among the elderly ages, but we also identified heavy impact of COVID-19 on the working population. Therefore, we recommend further evaluation of age-adjusted mortality for all States and inclusion of variables like gender, socio-economic status for standardization while identifying at-risk populations and implementing priority public health actions.

Emerging and re-emerging viral infections in India.

The number of outbreaks have progressively increased since many years in India. In this era of globalization and rapid international travel, any infectious disease in one country can become a potential threat to the entire globe. Outbreaks of Nipah, Zika, Crimean-Congo Haemorrhagic Fever and Kyasanur Forest Disease have been reported since a decade and now we are facing COVID-19 pandemic. One of the challenges in the prevention of these outbreaks is that as the cases decrease, the felt need declines, the public demand decreases and the mitigation responses get overshadowed by the need of emergency responses elsewhere. The One Health approach is a movement to promote alliance between medicine field, veterinary medicine and environmental sciences to upgrade the health of humans, animals, and ecosystem. The data in this article is compiled from different websites and publications of World Health Organization (WHO), Centre for Disease Control and Prevention (CDC), Integrated Disease Surveillance Programme (IDSP), grey literature and media. There is an urgent need for better surveillance and disease burden assessments in the country and to gain detailed insights into vector biology, factors of environment influencing the diseases, mapping of endemic areas, strengthen intersectoral coordination, infection control practices, and ensure use of Personal Protective Equipment's (PPE) and availability of drugs and vaccines to handle the outbreaks in a better way.