|Year : 2013 | Volume
| Issue : 1 | Page : 14-19
Assessment of integrated disease surveillance and response strategy implementation in selected Local Government Areas of Kaduna state
Aisha A Abubakar1, Mohammad N Sambo2, Suleman H Idris2, Kabir Sabitu2, Patrick Nguku3
1 Department of Community Medicine, Ahmadu Bello University, Zaria; Nigeria Field Epidemiology and Laboratory Training Programme, Nigeria
2 Department of Community Medicine, Ahmadu Bello University, Zaria, Nigeria
3 Nigeria Field Epidemiology and Laboratory Training Programme, Nigeria
|Date of Web Publication||18-Oct-2013|
Aisha A Abubakar
Department of Community Medicine, Ahmadu Bello University, Zaria
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Widespread epidemics of yellow fever and cerebrospinal meningitis across the African sub region in the 1990s were largely attributed to poor surveillance systems which were neither able to detect communicable diseases on time nor mount an effective response. Effective communicable disease control relies on effective response systems which are dependent upon effective disease surveillance. Integrated Disease Surveillance and Response strategy (IDSR) was adopted by the AFRO members of the World Health Organization (WHO) to improve surveillance activities.
Aim: This study was conducted to assess IDSR implementation in selected Local Government Areas (LGAs) of Kaduna state.
Settings and Design: Kaduna state is located in Northern Nigeria. It shares borders with the states of Sokoto, Katsina, Niger, Kano, Bauchi and Plateau. Based on the 2006 census projections, it has a population of 6.63 million. The study was a cross-sectional descriptive study.
Materials and Methods: An interviewer administered questionnaire of an adaptation of the World Health Organization Protocol for the Assessment of National Communicable Disease Surveillance and Response systems was used. Data analysis was carried out using Epi Info statistical package version 3.5.1.
Results: About a third of the health facilities (38%) did not have any case definition for the priority diseases. About 76% of the health facilities had electricity available from the National Grid. Seventy one percent have standby generators, out of which 67% were functional. Sixty two percent of health facilities had calculators available for data management while 29% had computers and printers available. No form of data analysis was available in 81% of the health facilities, analysis of data were however available in all 3 LGAs studied. A reporting system was available in 57% of health facilities. Thirteen percent of the health facilities reported receiving feedback from the LGAs. There was no feedback from the state to the LGAs, nor was there feedback from the national to the state level.
Conclusion: The implementation of IDSR in Kaduna state is poor. Resources are insufficient and although some structures are present on ground like the presence of reporting mechanism, feedback is poor from the higher to lower levels. Standard case definitions are not used in all health facilities for all priority diseases. Standard case definitions should be made available and used in all health facilities.
Keywords: Assessment, integrated disease surveillance and response, implementation
|How to cite this article:|
Abubakar AA, Sambo MN, Idris SH, Sabitu K, Nguku P. Assessment of integrated disease surveillance and response strategy implementation in selected Local Government Areas of Kaduna state. Ann Nigerian Med 2013;7:14-9
|How to cite this URL:|
Abubakar AA, Sambo MN, Idris SH, Sabitu K, Nguku P. Assessment of integrated disease surveillance and response strategy implementation in selected Local Government Areas of Kaduna state. Ann Nigerian Med [serial online] 2013 [cited 2021 May 6];7:14-9. Available from: https://www.anmjournal.com/text.asp?2013/7/1/14/119981
| Introduction|| |
Worldwide, the emergence of new communicable diseases such as avian influenza as well as the re-emergence of tuberculosis has led to the recognition of the need for effective disease surveillance and response.  Widespread epidemics of yellow fever and cerebrospinal meningitis across the African sub region in the 1990s was largely attributed to poor surveillance systems which were neither able to detect communicable diseases on time nor mount an effective response.  Effective communicable disease control relies on effective response systems, which in turn depend on effective disease surveillance.  Surveillance has been defined as the process of systematic collection, collation and analysis of data with prompt dissemination to those who need to know, for relevant action to be taken. 
Before 1998, most African countries used a variety of vertical disease control programs for disease surveillance. Some of these programs were well funded, while others were in a state of collapse. Surveillance data were collected by programs under different authorities which led to disjointed and inefficient systems in which health workers used multiple complicated reporting formats with different terminologies and reporting mechanisms. This resulted in health workers becoming overloaded and demotivated. 
The World Health Organization (WHO), African region adopted the Integrated Disease Surveillance and Response (IDSR) strategy as a regional strategy in 1998. This was a paradigm shift, as in the integrated surveillance system, surveillance activities use similar structures, processes and personnel. ,,, In Nigeria, IDSR implementation started in June 2000 with an orientation workshop held to sensitize national program managers of vertical programs and partners on IDSR. In January 2001, a steering committee on IDSR was inaugurated to steer the implementation process. All the 36 states in the Federation, including the Federal Capital Territory are currently implementing IDSR. 
The Integrated Disease Surveillance system seeks to ensure that effective and functional systems are available at each level of the health system, from health facilities to Local Government Areas (LGAs), states and at the national level. IDSR focuses on the LGA level where information generated is used for timely action consequently leading to reduction of morbidity, disability and mortality. ,
A country where IDSR is functional would use standard IDSR case definitions to identify and report priority diseases; collect and use surveillance data to alert higher levels and trigger local action; investigate and confirm suspected outbreaks or public health events using laboratory confirmation, when indicated; analyze and interpret data collected in outbreak investigation and from routine monitoring of other priority diseases; use information from the data analysis to implement an appropriate response; provide feedback within and across levels of the health care system; and evaluate and improve the performance of surveillance and response systems. 
The flow of information in the IDSR system in Nigeria is from the health facility, where diseases that have epidemic potential, which are targeted for eradication and elimination, are reported immediately to the focal persons in the health facility and to the LGA. The LGA receive data from the health facilities, collate and send to the next level, the State Ministry of Health (SMOH). At the LGA level, analysis and feedback to health facilities is to be done. The Epidemiology unit of the SMOH collates data from the LGAs and forwards it to the Epidemiology Division of the Federal Ministry of Health (FMOH). At the SMOH, analysis and feedback to the health facilities and public is done as well as planning appropriate operations and strategies for disease control. At the FMOH, data is collated and forwarded to the statistics division, analysis and feedback is carried out, as well as planning for appropriate intervention based upon the results of analysis. 
The aim of the study was to assess the implementation of Integrated Disease Surveillance and Response (IDSR) in selected LGAs in Kaduna state.
| Materials and Methods|| |
Background of study area
The state of Kaduna is located in northern Nigeria. It shares borders with the states of Sokoto, Katsina, Niger, Kano, Bauchi and Plateau. It has a population of 6.63 million based on the 2006 census projections. Kaduna state is administratively divided into 23 Local Government Areas. There are several districts and wards in each LGA.
The state is divided into three senatorial zones: Northern (Zone 1), Central (Zone 2) and Southern Senatorial (Zone 3) zones. Zone 1 comprises of Zaria, Soba, Sabon Gari, Makarfi, Kudan, Ikara, Kubau and Lere LGAs. Zone 2 comprises of Birnin Gwari, Giwa, Chikun, Kaduna South, Kaduna North, Kajuru and Igabi LGAs. Zone 3 comprises of Zangon Kataf, Jama'a, Kauru, Kaura, Kachia, Sanga, Jaba and Kagarko LGAs. Kaduna state has 739 local government health facilities, 29 secondary care facilities and five tertiary hospitals.
Under the Integrated Disease Surveillance and Response system, all health facilities collate data on the priority disease and send to the Local Government Area Health office where they are located. The Health Department of the Local Government Area then collates the surveillance data and carries out some analysis and then sends the data to the State Epidemiology Unit of the State Ministry of Health. The Epidemiology Unit then collates surveillance data from all Local Government Areas in the state before sending the data to the Epidemiology Division of the Federal Ministry of Health. Some analysis is also carried out at state level.
The study was a cross-sectional descriptive study.
Selection of sites
The State Epidemiology Unit was selected for the study.
Three LGAs were selected. In each LGA, the following sites were selected: The LGA Health Office and 7 health facilities were purposively selected.
Multistage sampling was used. One LGA from each zone was selected first. The following LGAs were selected: Zaria LGA from Zone 1, Kaduna North in Zone 2 and Kachia LGA in Zone 3.
Next, 7 health facilities were selected by simple random sampling in each LGA.
Quantitative data was collected in this study using interviewer administered questionnaires administered to the Medical Officers in charge of the health facilities, the Disease Surveillance and Notification Officer at the LGA Health office and the State Epidemiologist.
Records and reports were also reviewed at the Health facilities, LGA Health Office and State Epidemiology Unit.
The tool used was adapted from the World Health Organization Protocol for the Assessment of National Communicable Disease Surveillance and Response systems. 
The tool was pretested at Sabon Gari LGA and corrections were made before data collection began.
Data collection began when approval was obtained from the Kaduna state Ministry of Health. Data was analyzed using Epi Info statistical package version 3.5.1, in consonance with the objectives of the study. Proportions were calculated at each level- health facility and LGA.
Prior to starting the study, approval was obtained from the Ethical and Scientific Committee of the Ahmadu Bello University Teaching Hospital, Zaria. Permission was obtained from the Kaduna State Ministry of Health. Informed consent was also obtained from the respondents.
| Results|| |
Resources available for IDSR at health facility, LGA and state level
About 76% of the health facilities had electricity available from the national grid. Seventy one percent had standby generators, out of which 67% were functional. Fourteen percent had bicycles available while 29% had motorcycles and cars available [Table 1]. Sixty two percent of health facilities had calculators available for data management, while 29% had computers and printers [Figure 1].
|Figure 1: Data management materials available for IDSR at health facility level|
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All 3 LGAs had electricity available from the national grid. 2 LGAs had standby generators available which were all functional. 2 LGAs had both bicycles and motorcycles available, out of which 31% and 42% respectively were functional [Table 2]. All LGAs had computers, but only 75% were functional. Sixty seven percent of LGAs had stationery, calculators and a printer available. None of the LGAs, however, had telephones available.
Electricity is available at the state level from the national grid and a functional standby generator is available. There is no transport available. Stationery is not available for data management. A calculator, computer and printer are available for data management. There is no statistical package available.
Use of standard IDSR case definitions to identify priority diseases at health facility level
About a third of health facilities (38%) did not have any case definition for the priority diseases [Table 3].
|Table 3: Use of standard IDSR case definitions to identify priority diseases at health facility level|
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Availability of data analysis on priority diseases at health facility, LGA and state level
Seventeen (81%) of the health facilities had no form of data analysis available [Table 4]. All the LGAs had data analysis available on the priority diseases. All the LGAs had data analysis by age & sex distribution and spot maps available for at least one priority disease. Only 1 LGA had a line graph available.
|Table 4: Availability of data analysis on priority diseases at health facility level|
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All the LGAs reported that they had used local data for prevention and control measures for diarrhoeal disease outbreak and measles outbreak.
At the State level, analysis of data on priority diseases was plotted by time (line graphs) as well as place (spot maps).
Availability of a reporting system and feedback mechanism on priority diseases at health facility, LGA and state level
Twelve (57%) of health facilities have a reporting system to the LGA in place [Table 5]. All 12 health facilities with an existing reporting system send in reports by hand delivery.
|Table 5: Availability of reporting system from health facility to LGA level|
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All LGAs reported sending reports to the state level. Two (67%) send their reports by hand delivery while 1 LGA reported sending monthly reports by mobile phone.
At the state level, reporting to the national level is through email.
Two (13%) primary health facilities reported receiving feedback from their respective LGAs. There were no feedback reports from the state to the LGA nor were there any form of feedback reported from the national level to the state level.
| Discussion|| |
An assessment of the implementation of the Integrated Disease Surveillance and Response (IDSR) in Kaduna state started with an assessment of resources available for IDSR. Health facilities were more likely to have calculators available (67%) than any other data management tool. This was similar to findings in Tanzania  and more than the figures of the 2001 assessment of surveillance in Nigeria, where 47% of health facilities had calculators available.  The findings were less than in Uganda, where 78% of health facilities had calculators.  Data management tools like calculators are an important resource, as they can be used for simple calculations and data analysis at the health facility, LGA and state level.
At the LGA level, 67% had stationery and calculators available, this was less than the findings in Tanzania, where all districts surveyed had calculators available.  All LGAs surveyed had computers available for data management, out of which 3 were functional. This was similar to other studies in Mozambique and Tanzania where all districts and provincial directorates studied had computers available. , The findings showed an improvement over the 2009 IDSR assessment in Nigeria, where 25% of LGAs had computers.  Computers are important data management tools for IDSR as they can be used for data entry and analysis. At the state level, a computer, printer and calculator were available for data management. Although there were no internet facilities available at the state level, reporting to the national level was by the use of internet facilities at internet cafes. This affords a relatively fast and cheap way of reporting, but the inconvenience of using commercial cafes can sometimes make this method unreliable, compared to having internet facilities available at the Epidemiology Unit of the state Ministry of Health.
Sixty two percent of health facilities had at least one standard IDSR case definition available; this was higher than the 35% reported in Tanzania  and similar to findings by Rumisha in Tanzania, where case definitions were not used for recording diagnosis in registers.  Another study in Tanzania by Mghamba, et al. found case definitions to be insufficient in the health facilities.  In Ghana, standard case definition pamphlets are distributed to health facilities for diagnosis and this increased the availability and use of case definitions at health facilities.  However, this differed from the assessment of surveillance in Nigeria in 2001, where no health facility had any case definition for any of the priority diseases  and the 2009 assessment of IDSR where 68% of health facilities did not have case definitions for any of the priority diseases.  Use of standard case definitions is very important as it allows for standardization of reporting across the country from all health facilities. Non use of standard case definitions would not allow proper tracking of the priority diseases across the country.
Nineteen percent of the health facilities had a form of data analysis on surveillance data available. This was higher than the 10% and 17% reported in Uganda and Nigeria respectively, , but lower than the 32% reported by Mghamba in Tanzania,  and much lower than the 41-78% reported in Ghana from 2004 to 2005  and the 20% reported in Nigeria and Kenya. , Analysis and interpretation of data at the health facility and LGA level is important and is one of the determinants of IDSR implementation. It allows for practical use of the data collected for surveillance at both health facility and LGA levels.
Over half (57%) of the health facilities have a reporting system in place for reporting to the LGA. Reports are sent by hand delivery, although other studies have reported increasing use of electronic reporting of surveillance data by email.  This may be connected to the unavailability of internet facilities at all levels. Although the state has no internet facilities, reporting to the national level was by email, using internet cafes. In the study, a clear reporting system was available at all levels compared to findings by Mghamba in Tanzania  where districts had no clear reporting mechanism. Thirteen percent of LGAs reported receiving feedback from LGAs; this was lower than that reported from Uganda and Tanzania. , There were no feedback from the state to the LGA, similar to findings from a peer review assessment.  This differed from findings in Mozambique and Tanzania where 50% of districts received feedback from the provincial level. , The state reported not receiving any feedback from the national level. This differed from findings in Nigeria in 2001 where 50% of states reported receiving feedback reports from the national level,  and in 2009 where 67% of states reported receiving feedback from the national level.  Lack of feedback from higher levels demotivates staff involved in reporting as they may not see the results of reporting, and may lead to a poor performance in future.
| Conclusion|| |
The implementation of IDSR in Kaduna state is poor. Resources are insufficient and there is poor feedback from the higher to the lower levels. Standard case definitions for priority diseases are not used in all health facilities.
| References|| |
|1.||Franco LM, Setzer J, Banke K. Improving performance of IDSR at district and facility levels: Experiences in Tanzania and Ghana in making IDSR operational. Bethesda, MD: The partners for reform plus project. Abt Associates 2006:13-5. |
|2.||Nsubuga P, Eseko N, Tadesse W, Ndayimirije N, Stella C, McNabb S. Structure and performance of infectious disease surveillance and response, United Republic of Tanzania, 1998. Bull World Health Organ 2002;80:196-203. |
|3.||World Health Organization. An Integrated approach to communicable disease surveillance. Weekly Epidemiological Record 2000;75:1-8. Available at http://who.int/docstore/wer/pdf/2000/wer7501.pdf [Last accessed on 2012 December 26]. |
|4.||World Health Organization. Protocol for the assessment of National Communicable Disease Surveillance and Response systems. 2001 WHO/CDS/CSR/ISR/2001-2:1-8. |
|5.||Sadiq LK. Overview of integrated disease surveillance. Bulletin of Epidemiology 2001;6:5-6. |
|6.||Federal Ministry of Health. National policy on IDSR, Federal Ministry of Health September 2005:1-7. |
|7.||World Health Organization. Guide for the use of core IDSR indicators in the African region, World Health Organization 2005:8-10. |
|8.||Epidemiology Division, Federal Ministry of Health. National technical guidelines for IDSR. Federal Ministry of Health 2002:1-15. |
|9.||Epidemiology Division, Federal Ministry of Health. Report on the assessment of disease surveillance system, epidemic preparedness and response in Nigeria. Federal Ministry of Health 2001:1-21. |
|10.||Centers for Disease Control and Prevention (CDC). Assessment of infectious disease surveillance-Uganda 2000. MMWR Morb Mortal Wkly Rep 2000;49:687-91. |
|11.||Mghamba JM, Mboera LE, Krekamo W, Senkoro KP, Rumisha SF, Shayo E, et al. Challenges of implementing an IDSR strategy using the current health management information system in Tanzania. Tanzan Health Res Bull 2004;6:57-63. |
|12.||Government of Mozambique and the World Health Organization. Assessment of epidemiological disease surveillance system in Mozambique, 13 th November-4 th December 2006. Government of Mozambique and the World Health Organization. p. 1-41. |
|13.||Federal Ministry of Health. Report on the assessment of the integrated disease surveillance and response implementation in Nigeria, July 2009 (Draft). Federal Ministry of Health. p. 1-63. |
|14.||Rumisha SF, Mboera LE, Senkoro KP, Gueye D, Mmbuji PK. Monitoring and evaluation of integrated disease surveillance and response in selected districts in Tanzania. Tanzan Health Res Bull 2007;9:1-11. |
|15.||World Health Organization. Peer Review Report on Integrated Disease Surveillance in Kaduna State, Nigeria, 2009. |
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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