scholarly journals Disease Surveillance System of Bangladesh: Combating Public Health Emergencies

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Mohammed Husain ◽  
Mahmudur Rahman ◽  
Asm Alamgir ◽  
M. Salim Uzzaman ◽  
Meerjady Sabrina Flora
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Communicable Disease ◽  
Control Unit ◽  
Communicable Diseases ◽  
Health Facilities ◽  
Surveillance Data ◽  
Public Health Emergencies ◽  
Disease Surveillance System

Objectivea) To observe trends and patterns of diseases of public health importance and responseb) To predict, prevent, detect, control and minimize the harm caused by public health emergenciesc) To develop evidence for managing any future outbreaks, epidemic and pandemicIntroductionDisease surveillance is an integral part of public health system. It is an epidemiological method for monitoring disease patterns and trends. International Health Regulation (IHR) 2005 obligates WHO member countries to develop an effective disease surveillance system. Bangladesh is a signatory to IHR 2005. Institute of Epidemiology, Disease Control and Research (IEDCR <www.iedcr.gov.bd>) is the mandated institute for surveillance and outbreak response on behalf of Government of the People’s Republic of Bangladesh. The IEDCR has a good surveillance system including event-based surveillance system, which proved effective to manage public health emergencies. Routine disease profile is collected by Management Information System (MIS) of Directorate General of Health Services (DGHS). Expanded Program of Immunization (EPI) of DGHS collect surveillance data on EPI-related diseases. Disease Control unit, DGHS is responsible for implementing operational plan of disease surveillance system of IEDCR. The surveillance system maintain strategic collaboration with icddrr,b.MethodsThe IEDCR is conducting disease surveillance in several methods and following several systems. Surveillance data of priority communicable disease are collected by web based integrated disease surveillance. It is based on weekly data received from upazilla (sub-district) health complex on communicable disease marked as priority. They are: acute watery diarrhea, bloody dysentery, malaria, kala-azar, tuberculosis, leprosy, encephalitis, any unknown disease. Government health facilities at upazilla (sub-district) send the data using DHIS2. During outbreak, daily, even hourly reporting is sought from the concerned unit.Moreover, IEDCR conducts disease specific specialized surveillance systems. Data from community as well as from health facilities are collected for Influenza, nipah, dengue, HIV, cholera, cutaneous anthrax, non-communicable diseases, food borne illness. Data from health facilities are collected for antimicrobial resistance, rotavirus and intussusception, reproductive health, child health and mortality, post MDA-surveillance for lymphatic filariasis transmission, molecular xenomonitoring for detection of residual Wucheria bancrofti, dengue (virological), emerging zoonotic disease threats in high-risk interfaces, leptospirosis, acute meningo-encephalitis syndrome (AMES) focused on Japanese encephalitis and nipah, unintentional acute pesticide poisoning among young children. Data for event based surveillance are collected from usual surveillance system as well as from dedicated hotlines (24/7) of IEDCR, media monitoring, and any informal reporting.Case detection is done by syndromic surveillance, laboratory diagnosed surveillance, media surveillance, hotline, cell phone-based surveillance. Dissemination of surveillance is done by website of IEDCR, periodic bulletins, seminar, conference etc. Line listing are done by rapid response teams working in the surveillance sites. Demographic information and short address are listed in the list along with clinical and epidemiological information. Initial cases are confirmed by laboratory test, if required from collaborative laboratory at US CDC (Atlanta). When the epidemiological trend is clear, then subsequent cases are detected by symptoms and rapid tests locally available.ResultsIn 2017, 26 incidents of disease outbreak were investigated by National Rapid Response Team (NRRT) of IEDCR. In the same year, 12 cases of outbreak of unknown disease was investigated by NRRT of IEDCR at different health facilities. Joint surveillance with animal health is being planned for detection and managing zoonotic disease outbreaks, following One Health principles. Department of Livestock, Ministry of Environment and icddrb are partners of the joint surveillance based on One Health principles.Disease Control unit of DGHS, district and upazilla health managers utilizes the disease surveillance data for public health management. They analyze also the surveillance data at their respective level to serve their purpose.ConclusionsA robust surveillance is necessary for assessing the public health situation and prompt notification of public health emergency. The system was introduced at IEDCR mainly for malaria and diarrhea control during establishment of this institute. Eventually the system was developed for communicable disease, and recently for non-communicable diseases. It is effectively used for managing public health emergencies. Notification and detection of public health emergency is mostly possible due to media surveillance.Data for syndromic surveillance for priority communicable diseases is often not sent timely and data quality is often compromised. Tertiary hospitals are yet to participate in the web based integrated disease surveillance system for priority communicable diseases. But they are part of specialized disease surveillances. Data from specialized surveillance with laboratory support is of high quality.Evaluation of the system by conducting research is recommended to improve the system. Specificity and sensitivity of case detection system should also be tested periodically.ReferencesCash, Richard A, Halder, Shantana R, Husain, Mushtuq, Islam, Md Sirajul, Mallick, Fuad H, May, Maria A, Rahman, Mahmudur, Rahman, M Aminur. Reducing the health effect of natural hazards in Bangladesh. Lancet, The, 2013, Volume 382, Issue 9910IEDCR. At the frontline of public health. updated 2013. www.iedcr.gov.bdAo TT, Rahman M et al. Low-Cost National Media-Based Surveillance System for Public Health Events, Bangladesh. Emerging Infectious Diseases. Vol 22, No 4. 2016.<www.iedcr.gov.bd> accessed on 1 Oct 2018. 

scholarly journals Potential Early Identification of a Large Campylobacter Outbreak Using Alternative Surveillance Data Sources: Autoregressive Modelling and Spatiotemporal Clustering (Preprint)

2020 ◽  
Author(s):  
Mehnaz Adnan ◽  
Xiaoying Gao ◽  
Xiaohan Bai ◽  
Elizabeth Newbern ◽  
Jill Sherwood ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Case Reports ◽  
Surveillance Data ◽  
Data Sources ◽  
Google Trends ◽  
School Absenteeism ◽  
Disease Surveillance System ◽  
Spatiotemporal Clustering

BACKGROUND Over one-third of the population of Havelock North, New Zealand, approximately 5500 people, were estimated to have been affected by campylobacteriosis in a large waterborne outbreak. Cases reported through the notifiable disease surveillance system (notified case reports) are inevitably delayed by several days, resulting in slowed outbreak recognition and delayed control measures. Early outbreak detection and magnitude prediction are critical to outbreak control. It is therefore important to consider alternative surveillance data sources and evaluate their potential for recognizing outbreaks at the earliest possible time. OBJECTIVE The first objective of this study is to compare and validate the selection of alternative data sources (general practice consultations, consumer helpline, Google Trends, Twitter microblogs, and school absenteeism) for their temporal predictive strength for Campylobacter cases during the Havelock North outbreak. The second objective is to examine spatiotemporal clustering of data from alternative sources to assess the size and geographic extent of the outbreak and to support efforts to attribute its source. METHODS We combined measures derived from alternative data sources during the 2016 Havelock North campylobacteriosis outbreak with notified case report counts to predict suspected daily Campylobacter case counts up to 5 days before cases reported in the disease surveillance system. Spatiotemporal clustering of the data was analyzed using Local Moran’s I statistics to investigate the extent of the outbreak in both space and time within the affected area. RESULTS Models that combined consumer helpline data with autoregressive notified case counts had the best out-of-sample predictive accuracy for 1 and 2 days ahead of notified case reports. Models using Google Trends and Twitter typically performed the best 3 and 4 days before case notifications. Spatiotemporal clusters showed spikes in school absenteeism and consumer helpline inquiries that preceded the notified cases in the city primarily affected by the outbreak. CONCLUSIONS Alternative data sources can provide earlier indications of a large gastroenteritis outbreak compared with conventional case notifications. Spatiotemporal analysis can assist in refining the geographical focus of an outbreak and can potentially support public health source attribution efforts. Further work is required to assess the location of such surveillance data sources and methods in routine public health practice.

scholarly journals Potential Early Identification of a Large Campylobacter Outbreak Using Alternative Surveillance Data Sources: Autoregressive Modelling and Spatiotemporal Clustering

10.2196/18281 ◽  
2020 ◽  
Vol 6 (3) ◽  
pp. e18281
Author(s):  
Mehnaz Adnan ◽  
Xiaoying Gao ◽  
Xiaohan Bai ◽  
Elizabeth Newbern ◽  
Jill Sherwood ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Case Reports ◽  
Surveillance Data ◽  
Data Sources ◽  
Google Trends ◽  
School Absenteeism ◽  
Disease Surveillance System ◽  
Spatiotemporal Clustering

Background Over one-third of the population of Havelock North, New Zealand, approximately 5500 people, were estimated to have been affected by campylobacteriosis in a large waterborne outbreak. Cases reported through the notifiable disease surveillance system (notified case reports) are inevitably delayed by several days, resulting in slowed outbreak recognition and delayed control measures. Early outbreak detection and magnitude prediction are critical to outbreak control. It is therefore important to consider alternative surveillance data sources and evaluate their potential for recognizing outbreaks at the earliest possible time. Objective The first objective of this study is to compare and validate the selection of alternative data sources (general practice consultations, consumer helpline, Google Trends, Twitter microblogs, and school absenteeism) for their temporal predictive strength for Campylobacter cases during the Havelock North outbreak. The second objective is to examine spatiotemporal clustering of data from alternative sources to assess the size and geographic extent of the outbreak and to support efforts to attribute its source. Methods We combined measures derived from alternative data sources during the 2016 Havelock North campylobacteriosis outbreak with notified case report counts to predict suspected daily Campylobacter case counts up to 5 days before cases reported in the disease surveillance system. Spatiotemporal clustering of the data was analyzed using Local Moran’s I statistics to investigate the extent of the outbreak in both space and time within the affected area. Results Models that combined consumer helpline data with autoregressive notified case counts had the best out-of-sample predictive accuracy for 1 and 2 days ahead of notified case reports. Models using Google Trends and Twitter typically performed the best 3 and 4 days before case notifications. Spatiotemporal clusters showed spikes in school absenteeism and consumer helpline inquiries that preceded the notified cases in the city primarily affected by the outbreak. Conclusions Alternative data sources can provide earlier indications of a large gastroenteritis outbreak compared with conventional case notifications. Spatiotemporal analysis can assist in refining the geographical focus of an outbreak and can potentially support public health source attribution efforts. Further work is required to assess the location of such surveillance data sources and methods in routine public health practice.

Performance Assessment of a Communicable Disease Surveillance System in Response to the Twin Earthquakes of East Azerbaijan

2015 ◽  
Vol 9 (4) ◽  
pp. 367-373 ◽  
Author(s):  
Javad Babaie ◽  
Ali Ardalan ◽  
Hasan Vatandoost ◽  
Mohammad Mehdi Goya ◽  
Ali Akbari Sari
Keyword(s):  
Data Quality ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Communicable Disease ◽  
Communicable Diseases ◽  
Disease Surveillance System ◽  
Health Authorities ◽  
Control And Prevention ◽  
Set Up ◽  
East Azerbaijan

AbstractObjectiveFollowing the twin earthquakes on August 11, 2012, in the East Azerbaijan province of Iran, the provincial health center set up a surveillance system to monitor communicable diseases. This study aimed to assess the performance of this surveillance system.MethodsIn this quantitative-qualitative study, performance of the communicable diseases surveillance system was assessed by using the updated guidelines of the Centers for Disease Control and Prevention (CDC). Qualitative data were collected through interviews with the surveillance system participants, and quantitative data were obtained from the surveillance system.ResultsThe surveillance system was useful, simple, representative, timely, and flexible. The data quality, acceptability, and stability of the surveillance system were 65.6%, 10.63%, and 100%, respectively. The sensitivity and positive predictive value were not calculated owing to the absence of a gold standard.ConclusionsThe surveillance system satisfactorily met the goals expected for its setup. The data obtained led to the control of communicable diseases in the affected areas. Required interventions based on the incidence of communicable disease were designed and implemented. The results also reassured health authorities and the public. However, data quality and acceptability should be taken into consideration and reviewed for implementation in future disasters. (Disaster Med Public Health Preparedness. 2015;9:367–373)

scholarly journals Evaluation of First Electronic Case Reports received in Illinois

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Stacey Hoferka
Keyword(s):  
Public Health ◽  
Case Report ◽  
Race And Ethnicity ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Communicable Disease ◽  
Case Reports ◽  
Production Environment ◽  
Provider Group ◽  
Disease Surveillance System

ObjectiveComparison of content in eCR and ELR cases reportingReview technical challenges and strategies for data managementIntroductionCommunicable disease reporting from providers can be a time-consuming process that results in delayed or incomplete reporting of infectious diseases, limiting public health's ability to respond quickly to prevent or control disease. The recent development of an HL7 standard for automated Electronic initial case reports (eICR) represents an important advancement for public health surveillance. The Illinois Department of Public Health (IDPH) participated in a pilot with the Public Health Informatics Institute and an Illinois-based provider group to accept eICR reports for Gonorrhea and Chlamydia.MethodsThe provider group working with their EHR vendor submitted a batch of CT and GC reports directly to IDPH in September 2017 according to the published eICR standard. A summary of the provider and PHII work has been presented previously in the STI eCR Learning Community. The eICR reports received from the provider were compared to case report data in the communicable disease surveillance system, I-NEDSS. Data was extracted from I-NEDSS that included race and ethnicity, timing of specimen collection, result, ELR submission surveillance action and treatment.ResultsIDPH received a batch of 89 files containing 77 unique persons, with 54 chlamydia (CT), 13 Gonorrhea (GC) and 10 co-infected case reports. The communicable disease surveillance system had captured 76 (98.7%) of the persons reported in the pilot. Among those, an Electronic Laboratory Report (ELR) was received for 72 (95%) cases, on average within 1 day of the lab report date. Data in I-NEDSS had a completion of 45% for race and ethnicity compared to 99% for race and 92% for ethnicity in the eICR files. Information on treatment in the surveillance system was reported for 18 (24%) cases compared to 67 (87%) cases.ConclusionsThis pilot was the first submission of real patient data submitted using the eICR standard to IDPH. Data was more complete from provider eICR reports for key demographic of race and ethnicity and treatment. A comparison with the current surveillance system showed near complete and timely case capture from ELR data. Integrated reporting of both ELR and eICR can produce a more complete case report through automated submissions and potentially reduce burden of data collection on health department communicable disease investigators. As public health reporting moves in this direction, public health agencies will have some substantial tasks to correctly ingest, map and interpret the increased amounts of information that are contained in the eICR. Further, the advantages of case reporting will be dependent on automated processes within the communicable disease system to merge data and apply business rules to automatically process completed case reports for high volume diseases, such as STIs. This work will continue as providers are ready to submit reports from different vendor products from a near real-time production environment.

scholarly journals Evaluation of Measles Surveillance Systems in Ginnir District, Bale Zone, Southeast Ethiopia: A Concurrent Embedded Mixed Quantitative/Qualitative Study 

2020 ◽  
Author(s):  
Falaho Sani ◽  
Mohammed Hasen ◽  
Mohammed Seid ◽  
Nuriya Umer
Keyword(s):  
Public Health ◽  
Qualitative Study ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Health Facilities ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Southeast Ethiopia ◽  
Bale Zone

Abstract Background: Public health surveillance systems should be evaluated periodically to ensure that the problems of public health importance are being monitored efficiently and effectively. Despite the widespread measles outbreak in Ginnir district of Bale zone in 2019, evaluation of measles surveillance system has not been conducted. Therefore, we evaluated the performance of measles surveillance system and its key attributes in Ginnir district, Southeast Ethiopia.Methods: We conducted a concurrent embedded mixed quantitative/qualitative study in August 2019 among 15 health facilities/study units in Ginnir district. Health facilities are selected using lottery method. The qualitative study involved purposively selected 15 key informants. Data were collected using semi-structured questionnaire adapted from Centers for Disease Control and Prevention guidelines for evaluating public health surveillance systems through face-to-face interview and record review. The quantitative findings were analyzed using Microsoft Excel 2016 and summarized by frequency and proportion. The qualitative findings were narrated and summarized based on thematic areas to supplement the quantitative findings.Results: The structure of surveillance data flow was from the community to the respective upper level. Emergency preparedness and response plan was available only at the district level. Completeness of weekly report was 95%, while timeliness was 87%. No regular analysis and interpretations of surveillance data, and the supportive supervision and feedback system was weak. The participation and willingness of surveillance stakeholders in implementation of the system was good. The surveillance system was found to be useful, easy to implement, representative and can accommodate and adapt to changing conditions. Report documentation and quality of data was poor at lower level health facilities. Stability of the system has been challenged by shortage of budget and logistics, staff turnover and lack of update trainings.Conclusions: The surveillance system was acceptable, useful, simple, flexible and representative. Data quality, timeliness and stability of the system were attributes that require improvement. The overall performance of measles surveillance system in the district was poor. Hence, regular analysis of data, preparation and dissemination of epidemiological bulletin, capacity building and regular supervision and feedback are recommended to enhance performance of the system.

The Geographical Matrix

2009 ◽  
Author(s):  
A. D. Cliff ◽  
M.R. Smallman-Raynor ◽  
P. Haggett ◽  
D.F. Stroup ◽  
S.B. Thacker
Keyword(s):  
Public Health ◽  
Disease Surveillance ◽  
Communicable Disease ◽  
Communicable Diseases ◽  
League Of Nations ◽  
Morbidity And Mortality ◽  
Significant Public Health ◽  
Degree Of Certainty ◽  
The Times ◽  
Health Organization

A historical–geographical exploration of disease emergence is confronted by a series of fundamental questions: Which diseases have emerged? When? And where? For some high-profile diseases, such as Legionnaires’ disease, Ebola viral disease, and severe acute respiratory syndrome (SARS), the first recognized outbreaks are well documented in the scientific literature and the space–time coordinates of these early events can be fixed with a high degree of certainty. But, for some other diseases—especially those that, over the decades, have periodically resurfaced as significant public health problems—the times and places of their rise to prominence can be harder to specify. Accordingly, in this chapter we undertake a content analysis of three major epidemiological sources to identify patterns in the recognition and recording of communicable diseases of public health significance in the twentieth and early twenty-first centuries. Our analysis begins, in Section 3.2, with an examination of global and world regional patterns of communicable disease surveillance as documented in the annual statistical reports of the League of Nations/World Health Organization, 1923–83. In Section 3.3, we turn to the US Centers for Disease Control and Prevention’s (CDC’s) landmark publication Morbidity and Mortality Weekly Report (MMWR) to identify ‘headline trends’ in the national and international coverage of communicable diseases, 1952–2005. Finally, in Section 3.4, the inventory of epidemic assistance investigations (Epi-Aids) undertaken by CDC’s Epidemic Intelligence Service (EIS), 1946– 2005, provides a unique series of insights from the front line of epidemic investigative research. Informed by the evidence presented in these sections, Section 3.5 concludes by specifying the regional–thematic matrix of diseases for analysis in Chapters 4–9. The systematic international recording of information about morbidity and mortality from disease begins with the Health Organization of the League of Nations, established in the aftermath of the Great War. The first meeting of the Health Committee of the Health Section of the League took place in August 1921 to consider ‘the question of organising means of more rapid interchange of epidemiological information’ (Health Section of the League of Nations 1922: 3).

scholarly journals Notifiable diseases after implementation of COVID-19 public health prevention measures in Central Queensland, Australia

2021 ◽  
Vol 45 ◽  
Author(s):  
Odewumi Adegbija ◽  
Jacina Walker ◽  
Nicholas Smoll ◽  
Arifuzzaman Khan ◽  
Julieanne Graham ◽  
...  
Keyword(s):  
Public Health ◽  
Disease Surveillance ◽  
Communicable Disease ◽  
Communicable Diseases ◽  
Prevention Measures ◽  
Vector Borne Diseases ◽  
Vaccine Preventable Diseases ◽  
Notifiable Diseases ◽  
Health Measures ◽  
Travel Restrictions

The implementation of public health measures to control the current COVID-19 pandemic (such as wider lockdowns, overseas travel restrictions and physical distancing) is likely to have affected the spread of other notifiable diseases. This is a descriptive report of communicable disease surveillance in Central Queensland (CQ) for six months (1 April to 30 September 2020) after the introduction of physical distancing and wider lockdown measures in Queensland. The counts of notifiable communicable diseases in CQ in the six months were observed and compared with the average for the same months during the years 2015 to 2019. During the study’s six months, there were notable decreases in notifications of most vaccine-preventable diseases such as influenza, pertussis and rotavirus. Conversely, notifications increased for disease groups such as blood-borne viruses, sexually transmitted infections and vector-borne diseases. There were no reported notifications for dengue fever and malaria which are mostly overseas acquired. The notifications of some communicable diseases in CQ were variably affected and the changes correlated with the implementation of the COVID-19 public health measures.

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