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Research Article
Open Access Peer-reviewed

Completeness of Reporting in the Community-based Disease Surveillance and Notification System in Anambra State, Nigeria

Chijioke A Ezenyeaku, Chinomnso C Nnebue , Simeon A Nwabueze, Cyril C Ezenyeaku, Ifeanyi N Udedibia, Ifeoma C Iloghalu, Obiageli F Emelumadu
American Journal of Public Health Research. 2020, 8(3), 77-86. DOI: 10.12691/ajphr-8-3-1
Received April 02, 2020; Revised May 04, 2020; Accepted May 11, 2020

Abstract

Background: Community involvement in the disease surveillance and notification (DSN) systems aids in leveraging community structures for improved disease prevention and control. Objective: To determine the completeness of reporting in the CBSS in Anambra State, Nigeria. Materials and methods: This was a cross sectional descriptive mix method study of the CBSS in Anambra State. Quantitative data were obtained using pre-tested, semi-structured questionnaires, interview-administered on 360 community informants, selected by multistage sampling technique, while data on completeness of filling of the community registers were obtained using observation checklist. Analyses were with SPSS version 20 and associations were tested using Chi square, Fisher’s exact and t tests as appropriate. Level of statistical significance was set at 5%. Key informant interviews (KII) were conducted among selected DSN key officers. Data from KII were transcribed verbatim, thematic content analysis done and key quotes noted. Results: The completeness of reporting in the system was 28.1%. Factors such as the source of information on detected disease, record of detected disease kept by community informant in the last one year, the number of times reports were sent in the last one year, feedback received by community informants given to community members, volunteer benefit and satisfaction with being a community informant had associations with completeness (p < 0.05). At the univariate level, keeping records, giving feedbacks to the community and being satisfied with the CBSS were significant predictors of completeness. The KII findings, showed that the commonest reason for sub-optimal functioning of the CBSS was poor funding. Conclusions: This study revealed low level of completeness of reporting of notifiable diseases and sub-optimal functioning of the CBSS in the State. We recommend improved supervision, record keeping, information transmission process and funding of the CBSS in Anambra State.

1. Introduction

It has been observed that the quality of disease surveillance, especially in developing climes can improve if a community-based approach is adopted 1. The community-based surveillance system (CBSS) was initiated in Nigeria in 2010. This was following the recommendations of the technical consultation meeting on global eradication of poliomyelitis, that in areas with poor access to health facilities or low utilization rates, community-based activities should be integrated into surveillance for diseases of public health importance 2, 3.

Completeness of reporting notifiable diseases is a key performance measure of public health surveillance systems 4. It is an important indicator of effectiveness of reporting systems and is associated with the ability of the system to completely detect and respond to public health concerns 5. Completeness of reporting measures the proportion of those diagnosed with a notifiable condition that were reported to the appropriate public health authorities 6. It also measures the total number of sources of reporting that are expected to report notifiable diseases or conditions that actually reported 7 as well as the match between the expected minimum surveillance data requirement and what is reported 8, 9. Although the WHO recommends surveillance systems achieving targets of 80% completeness as acceptable 4, missing or incomplete data compromises the quality and reliability of information and lead to inaccurate disease management. As a result, outbreaks may go undetected, and other opportunities to identify and respond to public health problems may be missed.

Studies had been carried out on DSN in Anambra State 7, 10, nonetheless, there is a dearth of data on CBS to substantiate this claim in Nigeria and in most parts of the African sub-region. These studies were at the health facility level, lacked the community component and were limited in their representativeness 7, 10, 11, 12, 13. Even though findings by Nnebue et al., on the effectiveness of data collection and information transmission process for disease notification in Anambra State, Nigeria, showed that the completeness of reporting by health workers was 81.5% 7, it could still be improved for better performance.

The findings from this study are expected to contribute to bridging this knowledge gaps.

They are also expected to provide the information that will guide the policy makers in instituting reforms aimed at strengthening the existing CBSS in the State. This study was conducted to determine the completeness of reporting in the CBSS in Anambra State, Nigeria.

2. Methodology

2.1. Study Area

This study was carried out in Anambra State, South-Eastern Nigeria. According to the 2006 census, the State has a total population of 4,177,828 persons, comprising 2,117,984 males and 2,059,844 females, with a population density of approximately 868 persons per squared kilometres 14, with an annual population growth rate of 2.21 percent, while its current projected population is 5,527,809 persons 15.

The State hosts two tertiary health-care institutions, the Nnamdi Azikiwe University Teaching Hospital, Nnewi and the Chukwuemeka Odumegwu Ojukwu University Teaching Hospital, Awka. There are 33 secondary health facilities, 382 primary health centers (PHCs), 14 mission hospitals, 600 private hospitals, 186 maternity homes, 126 registered pharmaceutical premises, nine health training institutions, and 1500 licensed patent medicine vendors in the State 15.

The State has a functional M&E office with a trained M&E officer. Information on surveillance of notifiable diseases in the State are collected by the DSNOs at the LGAs through a network of health facility focal persons who collect and report information to them on all the targeted diseases using surveillance case definitions and designated reporting forms. The process is coordinated by the State Epidemiologist. After analysis of data at the State level, the information, is then sent to the Federal Ministry of Health and the WHO country office every month 17. The WHO supports the surveillance structure in the State by conducting active surveillance and verifying reported cases as part of the monitoring obligations of WHO member states vis-à-vis the 2015 International Health Regulations requirements 18.

2.2. Study Design

This was a cross-sectional descriptive study of the completeness of reporting in the CBSS in Anambra.

2.3. Study Population

This comprised the community informants, the DSN focal persons in the health facilities, the DSNOs in the LGAs, the State DSNO, the State Epidemiologist, the State M&E Officer and the WHO Coordinator in Anambra State.


2.3.1. Inclusion Criterion

Having participated in CBSS in the state for at least a year. This is because they would have functioned long enough to have an opinion and contribute meaningfully to the study.


2.3.2. Exclusion Criterion

Being too sick to participate in the study. For the purpose of this study, severity of ill health was graded on a scale of 1(one) to 5 (five), with 1 (one) being the lowest severity and 5 (five) being the highest severity. Participants who reported 4 (four) or 5(five) were deemed as being too sick to participate and were excluded from the study.

2.4. Sample Size Determination

The sample size of community informants for this study was determined using the Cochran formula for descriptive studies with populations greater than 10,000 19: n = where: n = the calculated minimum sample size; Z = Standard normal deviate at 95% confidence interval, set at1.96; p = proportion of respondents that sent in reports early (In a study carried out in the northern region of Ghana, 74% of the expected number of village monthly reports were received timely 20, so p= 0.74); q = the complementary proportion of p i.e. 1-p, and d = precision level set at 5% = 0.05. n=295.648 = 296.

However, the target population in this study was the community informants in Anambra State with an estimated population of 1320 21. Therefore, the final sample estimate (nf) was calculated using the formula 19: nf = where: nf = the desired sample size when the population is less than 10,000; n = the desired sample size when the population is more than 10,000; N = the estimate of the size of the target population = 1320; nf (the desired sample size when the population is less than 10,000) was thus - 241.7= 242.

An adjustment of the estimated minimum final sample size to cover for non-response was made by dividing the calculated minimum final sample size estimate (nf) by 1 - f, where f is the anticipated non-response rate. Therefore, anticipating a non-response rate of 10%. The adjusted sample size was = = = 269 respondents. The minimum sample size was increased to 360 in order to increase the power of the study.

2.5. Sampling Technique
2.5.1. Quantitative Aspect of the Study

Multi-stage sampling technique was used to enrol respondents into this study. Anambra State is made up of three senatorial zones (Anambra North, Anambra Central and Anambra South), 21 LGAs (7(seven) urban and 14 rural) and 330 wards (ranging from 10 - 20 wards per LGA). Each of these wards has 4 (four) community informants. Stage1 - Selection of local government areas: The 21 LGAs in the state were stratified into the 7(seven) urban and 14 rural LGAs, giving a ratio of 1: 2. Using proportionate allocation, 3(three) LGAs were selected from the urban stratum while 6(six) LGAs were selected from the rural stratum through simple random sampling technique by balloting procedure. Thus Onitsha South, Awka South, and Nnewi North LGAs were selected from the urban stratum while Oyi, Anambra East, Njikoka, Anaocha, Orumba North and Orumba South LGAs were selected from the rural stratum. Stage 2 - Selection of Wards: There are 20 wards in Awka South LGA, 17 wards in Onitsha South LGA, 10 wards in Nnewi North LGA, 15 wards in Oyi LGA, 15 wards in Anambra East LGA, 18 wards in Njikoka LGA, 19 wards in Anaocha LGA, 18 wards in Orumba North LGA and 18 wards in Orumba South LGA. Proportionate numbers of wards were selected from each of these selected LGAs using Bowler’s proportional allocation formula stated below as follows 22:

where Wn = Number of wards selected from each LGA; n = Minimum size for the study =360; ni = Population of each unit (i= 1- 4) i.e. (Total number of wards in the selected LGA); N =The total population i.e. (Total number of informants in all the selected LGAs) = 600. For Example, the number of wards selected for studying from Awka South LGA was = 12 wards. Stage 3 - Selection of community informants: From each of these selected wards, all the community informants met the eligibility criteria and were thus recruited into the study. Therefore in Awka South LGA for example, 48 respondents (12 wards x 4 community informants) were studied.


2.5.2. Qualitative Aspect of the Study:

Twenty two KII sessions were conducted on nine health facility focal persons (one selected from each of the nine selected LGAs through convenience sampling), nine DSNOs in the nine selected LGAs, the State DSNO, the State Epidemiologist, the M&E Officer and the State WHO Coordinator.

2.6. Study Instruments
2.6.1. Quantitative Study Instruments

A 46-item semi-structured questionnaire adopted and adapted from the WHO’s protocol for the assessment of national communicable disease surveillance and response systems (23), and available literature (24) were used to collect information from the respondents (community informants) on socio-demographic characteristics, completeness of reporting of CBSS among them and factors affecting completeness of reporting of CBSS. An observation checklist was used to collect data on the availability of surveillance tools, correctness and completeness of reporting.


2.6.2. Qualitative Study Instrument

A KII guide adapted from literature (20) was used to conduct the KII sessions on the i) health facility focal persons; ii). DSNOs; iii) M&E Officer; iv) State DSNO; v) State Epidemiologist and v) State WHO Coordinator.

2.7. Data Collection Methods
2.7.1. Quantitative Data Collection Methods

Questionnaires were administered to the community informants using face to face interviews conducted by trained research assistants. In order to ensure quality control, the researchers were present for in-process monitoring of data collection in most of the study sites. Collected data were entered into the computer. An observation checklist was also used.


2.7.2. Qualitative Data Collection Method

Key informant interview guides were used. The KII sessions were moderated by the principal researcher assisted by the note taker/operator of the audio recorder.

2.8. Data Management
2.8.1. Measurement of Variables

The main outcome / dependent variable for this study was completeness of reporting in the CBSS. The independent variables were factors affecting the completeness of reporting in the CBSS. Completeness of reporting was assessed using the proportion of expected reports received by the health facility focal persons or the DSNOs from the community informants within the last 3 months from the time of the survey. The proportion of the community informants registers with the minimum expected surveillance data within the last 3 months from the time of the survey served as proxy for the proportion of expected reports received by the health facility focal persons or the DSNOs from the community informants. Completeness of reporting ≥ 80% was considered optimal for the surveillance system while completeness of reporting < 80% was considered suboptimal 25. For the purpose of this study, the system is assumed to be functioning optimally if completeness and one of other indicators (such as timeliness) are up to ≥ 80% and to be functioning sub-optimally if both or any of these two indicators is not up to 80%.


2.8.2. Statistical Analysis

2.8.2.1. Quantitative data: The collected data were inspected for any data collection or coding errors. It was then entered into and analysed with the International Business Machines-Statistical Package for Social Sciences (IBM-SPSS) version 20 26. Frequency distribution of all relevant variables was developed. Means and proportions were calculated while associations between variables were tested using Chi square, Fisher’s exact test and t tests as appropriate. Level of statistical significance was set at p-value ≤ 0.05 for all inferential analysis and standard deviations.

2.8.2.2. Qualitative data: The audio recordings obtained from the KII sessions were transcribed verbatim and compared with the written notes of the note-taker in order to improve the reliability of the data obtained. Coding and analysis of the transcripts were done using thematic content analysis 27. Quotes from the participants that best described the various themes and sub-themes were stated.

3. Results

3.1. Results of the Quantitative Survey

A total of 360 questionnaires were administered to community informants in nine LGAs of the State. All the questionnaires were retrieved, giving a response rate of 100%. Table 1 summarizes the socio-demographic characteristics of the respondents. The mean age of the respondents was 40.5 ± 9.8 years. Majority of them were Ibos, females and traders, while only 3.1% of the respondents had no formal education.

Table 2 highlights the completeness of disease notification among the respondents. Most of the respondents (67.8%) did not keep records of the notifiable diseases they detected. Only 28.1% of the respondents completed their registers (exercise books) within the last three months from the time of this survey. The completeness of reporting was 28.1%.

Table 3 highlights the association between socio-demographic and selected factors and completeness of disease case notification among the respondents. Factors such as the source of information on detected disease, record of detected disease kept by community informant in the last one year, the number of times reports were sent in the last one year, feedback received by community informants given to community members, volunteer benefit from being a community informant and volunteer satisfied with being a community informant were found to have associations with completeness of disease case notification (p < 0.05).

Table 4 shows the factors that were found to be significantly associated with completeness of disease case notification among the respondents at the univariate level. Keeping records of notifiable diseases in the last one year, giving feedbacks to the community and being satisfied with the CBSS were found to be significant predictors of completeness of reporting (Exact = 278.292, p = 0.000; χ2 = 23.197, p = 0.021; χ2 = 13.131, p = 0.001).

Table 5 shows the factors that were found to be significantly associated with completeness of disease case notification among the respondents at the multivariate level, Completeness of disease case notification was over 1000 times more likely to be carried out by community informants who kept records of notifiable diseases (OR = 1475.694, CI = 217.804-9998.329), 4.2 times more likely in those who gave feedbacks to the community (OR = 4.202, CI = 1.245-14.186) and 2.3 times more likely in those who were satisfied with being community informants (OR = 2.322, CI = 1.387-3.886). The other variables failed to achieve statistical significance with completeness of reporting at this level (p > 0.05).

3.2. Results of the Qualitative Aspect of the Study

Consistent themes emerged from all the KII sessions. These include: the interactions of supervisors with the community informants, the contributions of the community informants to the success of CBSS, challenges faced generally, modalities for improving the CBSS and sustainability of the CBSS. The results with quotations include “I used to supervise those people that are around me because I don’t have much time as we lack staff here. But each time I have the time, I used to supervise those that are around me” (focal person 5 in a rural area). Many of the focal persons affirmed that the community informants had contributed to the success of DSN in the State in general though this has been sub-optimal because of the non-active participation of many of the community informants in the system. “Of course, the community informants have contributed to the success of disease surveillance and notification in the state. They have given us information on AFP cases in the community and within the last six months, they have given us not less than 18 confirmed cases of measles” (focal person 3 in an urban area). “.....There is one that used to be punctual at Ifite. Each time he sees a case that he doesn’t know about, he will call me on phone. I will then use my motorcycle to go and see the case. Only the same person has been sending reports to me often and on. He has sent in up to 3 or 4 measles cases but there has not been an AFP case. Others will begin to manage the case unless I visit them without notice. They will now say that this is what they think that they can do by themselves. They don’t seem to care even though I told them that they should report the case immediately they see them” (focal person 1 in a rural area). “The informants have contributed to the success of DSN generally but some of them are complaining that the reason they don’t report to me is because they don’t have enough credit or they don’t have transport fare to come and tell me” (focal person 8 in a rural area).

Other challenges mentioned by the respondents included non - possession of phones by some community informants, lack of means of transportation, and poor attitude to CBS in general. However at the background of all these was still financial constraint. “The main challenge is that of transport and some of them do not have phones. Even if they have phones, what of funds to make calls. But then it might just be all about commitment and altruism. If there is a way to help people, you will want these people to get that help. So it might not always be all about money” (focal person 2 in a rural area). “Financial constraint is the main problem or challenge. Even the state will always tell you that they don’t have money. When you invite them to come and supervise us, they will tell you that they don’t have money to come to supervise us in the field. If you call them for case verification, they will not come. At the end of the day, it is only WHO that will come to verify the case” (DSNO 6 in a rural area).“You know that these people are not being paid on a regular basis. They are just volunteering to do the job. This means that whenever they like, they report. This is unlike when you hope to get a reward for working” (DSNO 5 in a rural area). “If the state can help the disease cases by providing anything at all, e.g. drugs, it will go a long way in encouraging the system to work. If we have two or three donors like WHO put in place so that they will be sponsoring the programme both in cash and in kind and every other thing required to carry out surveillance, there will be a great improvement in the system” (DSNO 5 in a rural area).

If the state and the donor agencies can be giving them stipend on a monthly basis, it will encourage them further. Whenever they come around to sign off the stipend, they will remember that they have a job at hand. It will also give us the right to demand to see what they have achieved within the time limit. It will also be good to provide adequate numbers of IEC material e.g. posters with the case definitions, so that when they display them in their work places, they will be reminded of them constantly” (DSNO 2 in a rural area). “CBS is working in the state and is contributing to the success of DSN in general because the recent LGA-based assessment done by WHO on IDSR revealed that most of the notifications came from the community to the LGA” (state M&E officer). “The engagement of community informants has contributed to the completeness of reporting in the state. They have been reporting cases which have been documented. At times even some parents report directly to the health facilities and these are recorded. We see all these when we analyze the pattern of reporting” (state WHO Coordinator). To strengthen the system, they need to give some encouragements to these community informants by if it is possible, giving them regular stipends so that they would now take it as a statutory function they need to fulfil. If they know that each month they are paid about ₦500, it becomes a commitment. You can say, every month call this person and tell him there’s no case or there’s a case. Giving them regular monthly stipend also gives you the moral justification to expect reports from them regularly. Otherwise it is you who will keep on calling them and asking them if they have cases” (state WHO coordinator).

4. Discussion

This was a cross sectional descriptive mix method study that determined the completeness of reporting of the CBSS in Anambra State, Nigeria. The index research findings showed that the completeness of reporting of notifiable disease was 28.1%. An effective DSN system requires that there be completeness of reporting among other indicators. The sub-optimal completeness of reporting obtained in this study shows that the system lacks the capacity to provide a comprehensive and representative picture of the health situation in the communities. This finding is similar to those in a study by Kyei-Faried et al., in Ghana 28. It is however contrary to those from studies elsewhere where CBS achieved appreciable levels of completeness of reporting ranging from 59% - 95.6% 20, 29, 30, 31. This variation in findings could be linked to differences in study methodologies.

Completeness of reporting should ideally be assessed from records at the health facility level 29. However, proxy data in the form of community informant registers with the minimum expected surveillance data within the last 3 months from the time of the survey was used. This was done to contend the lack of clarity in the channel of reporting. This may have led to the low value obtained for completeness of reporting in this study since some community informants who detected and notified disease cases may not have recorded them in their registers. This however is the true picture as findings from the results of the KIIs in the index study confirm that many community informants were not committed to fulfilling their duties in the CBSS and that only few of them report the cases they detect. For instance, “.....There is one that used to be punctual at Ifite. Each time that he sees a case that he doesn’t know about, he will call me on phone.... Only the same person has been sending reports to me often and on.... Others will begin to manage the case unless I visit them without notice. They will now say that this is what they think that they could do by themselves. They don’t seem to care even though I told them that they should report the cases immediately they see them” (focal person 1 in a rural area) The implication for such a low level of completeness of reporting as obtained in this study is the lack of reliability in the quality of generated data and the inaccuracies in disease evaluation and management accruing therefrom. If the desired quality of disease surveillance data is to be obtained at the community level, then there must be a reorientation of the community informants on the principles of CBSS as well as the need to streamline the channels of reporting in the system in the state as obtained in some other places 29.

This study also examined the influence of socio-demographic and some selected factors on the completeness of reporting of the CBSS in Anambra State. The age, gender, educational status and occupation of the respondents were found not to be significantly associated with completeness of reporting in this study. There was however a direct relationship between levels of knowledge of the respondents on CBSS with completeness of reporting in this study, a finding similar to those seen in other studies 32, 33. Even though no statistical significance was found, it posits that the community informants are knowledgeable about CBS and could successfully detect and report notifiable diseases as completely as expected.

Providing adequate training increases the awareness and knowledge of the community informants and enables them to report cases to the appropriate authorities in a more complete manner 29, 34, 35, 36, 37. Almost all the respondents in this study have been trained at least once on the principles and practice of CBSS. This could be an explanation for the high level of knowledge exhibited by the respondents in this study. This explanation is buttressed by the findings from the results of the KIIs which affirmed that the informants receive trainings at least once a year. This finding in the index study is similar to those from several other studies which showed that providing trainings for community informants enhanced their knowledge base and resulted in improvement in their diagnostic abilities 29, 37, 38. Providing training for community informants however had no statistically significant association with completeness of notifying diseases in this study. In the same vein, supportive supervision for the volunteers helps to strengthen their motivation, It also reinforces the knowledge they have gained as well as ensures that the right skills are used appropriately, that the necessary logistics are in place and that planned activities are implemented according to schedule 20, 28, 35, 39, 40. This study has shown there was no statistically significant association between means through which diseases were notified and completeness of reporting in this study. Keeping of records by the community informants was found to be a sign of completeness of reporting in this study. This is consistent with findings from some other studies 20, 41. After adjusting for potential confounders, keeping of records was found to be an independent predictor of completeness of reporting in this study. This finding is comparable to the 33.8% reported by Ababa in the pastoralist and semi-pastoralist communities in Ethiopia 30 and could indicate that adequate number of detected diseases may not have been reported from the community and is as shown in this study where the completeness of reporting was only 28.1%.

The low rate of record keeping observed in this study may be because majority of the respondents (59.4%) mentioned that they do not possess registers. The findings from the KIIs in this study show that this is rarely done probably because of the lack of the moral justification to demand any performance output (record keeping) from individuals who are not provided with regular stipends. Moreover, findings from the KIIs in the index study also show that some supervisors rarely interact with the community informants or encourage them to be more active. This situation could however be ameliorated by proper accreditation of the volunteers.

This study also revealed a statistically significant association between volunteer satisfaction with being a community informant and completeness of disease notification. This is because a worker satisfied with his job is more likely to be motivated to be more productive. Several studies report that providing incentives which may be financial or non-financial has been shown to keep volunteers satisfied 20, 35, 36, 39, 42, 43, 44. Findings from the results of the KIIs across all the levels of the CBSS in this study emphasize the need to provide regular monthly stipend to the community informants and to increase the stipend attached to notifying diseases. This they said will boost the morale of the community informants and encourage them to participate more actively in CBS. It has been said that an individual’s real motivation results from their personal accomplishments through the challenge of work itself and not necessarily from the working conditions in the environment. However, for the individual to function optimally, the working conditions must be made adequately enabling 45. Therefore the government should make provisions for adequate amounts of stipends or incentives to be given to the community informants in order to make the system more functional.

Strength and limitations: The strength of this study derives from the fact that it employed a mix method survey to provide detailed information on the characteristics and perceptions of the participants. The study is however limited in that completeness of reporting by the community informants should ideally be assessed from the records at the health facility level. However, due to lack of clarity in the channel of reporting in the CBSS, proxy data in the form of community informant registers with the minimum expected surveillance data within the last three months from the time of the survey was used to assess completeness of reporting. This could be subject to information bias.

5. Conclusions

This study has shown that the completeness of reporting of notifiable diseases in the CBSS in Anambra State is very low, and implies that the system is functioning sub-optimally. The age, gender, educational status and occupation of the respondents were found not to be significantly associated with completeness of reporting in this study but there was a direct relationship between levels of knowledge of the respondents on CBSS with completeness of reporting in this study. The commonest reason given for the sub-optimal functioning of the CBSS in the State from the KII was lack of funds. Other important factors influencing the completeness of the CBSS in this study were the means through which detected diseases were notified, the availability of supervisors for community informants, keeping of records by community informants and giving feedback to the community. Based on the above findings, the researchers recommend as follows: The logistics needed for adequate record keeping by the community informants should be fully provided by the organizers of the programme. This will motivate them to keep proper records of all the notifiable diseases. Mandatory weekly reporting to nearby health facilities, including zero reporting, should also be demanded from the community informants. This will make for a more complete and representative data reporting from the CBSS. The channels of reporting in the CBSS in the state, especially at the peripheral level, should be properly streamlined, and at least all the government-owned health facilities should be involved in the CBSS so that the community informants could have easy access to them. Adequate amounts of stipends or incentives should also be provided by the government and other relevant authorities across all the levels of the CBSS. This will motivate all players in the system and make for a more functional CBSS.

Funding

The authors have no support or funding to report.

Competing Interests

The authors declare that they have no competing interests.

Ethics Approval and Consent to Participate

Ethical approval for this study was obtained from the Nnamdi Azikiwe University Teaching Hospital Ethics Committee. Permission to conduct the study was obtained from the State Ministry of Health and the selected Local Government PHC Departments. In addition, verbal and written informed consents were obtained freely and without coercion from all the respondent.

Authors' Contributions

This work was carried out in collaboration among all authors. All authors read and approved the final manuscript.

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[14]  Nigeria data portal. Nigeria population census. 2006. Available from: https://www.nigeria.opendataforafrica.org/xspplpb/nigeria-census. [Accessed June 8, 2017].
In article      
 
[15]  National bureau of statistics. Nigeria’s population now 193.3 million. 2016. Available from: http://www.nigerianstat.gov.ng/ [Accessed November 12, 2017).
In article      
 
[16]  Anambra State Ministry of Health. Anambra State government strategic health development plan (2010-2015). 2010. Available from: www.mamaye.org/sites/default/files/.../ANAMBRA%20SSHDP%2015012010.pdf. [Accessed August 15, 2016].
In article      
 
[17]  International Federation of Red Cross and Red Crescent Societies. Community-based surveillance - Guiding principles. 2017. Available from: www.cruzrojazika.org/wpcontent/uploads/.../CommunityBasedSurveillance_Global_LR.p..[Accessed October 20, 2017].
In article      
 
[18]  World Health Organization. International Health Regulations (2005). 3rd ed. Geneva: The Organization; 2016. Available from: http://www.who.int/topics/internationalhealth_regulations/en/. [Accessed July 29, 2016].
In article      
 
[19]  Araoye MO. Research methodology with statistics for health and social sciences. 2nd ed. Illorin: Nathadex Publications; 2008. p. 115-22.
In article      
 
[20]  Maes E, Zimicki S. An evaluation of community-based surveillance in the northern region of Ghana. 2000. Available from: http/www.unicef.org/evaldatabase/ index _ 14293.html. [Accessed July 26, 2016].
In article      
 
[21]  Anambra State Ministry of Health - Office of the state Epidemiologist. Community informants profile. 2016. Pg 1- 20.
In article      
 
[22]  Bowler’s proportional allocation formula. In. Pandey R, Verma MR. Samples allocation in different strata for impact evaluation of developmental programme. Rev. Bras. Biom. São Paulo, 2008; 26(4), p.103-112.
In article      
 
[23]  WHO/CDS/CSR/ISR. Protocol for the Assessment of National Communicable Disease Surveillance and Response Systems. 2001. Available from: www.who.int/csr/resources/publications/surveillance/whocdscsrisr20012.pdf. [Accessed January 26, 2017].
In article      
 
[24]  Aniwada EC, Obionu CN. Disease surveillance and notification, knowledge and practice among private and public primary health care workers in Enugu State, Nigeria: A comparative study. Br J Med Med Res. 2016;13(3):1-10.
In article      View Article
 
[25]  Federal Ministry of Health. National policy on integrated disease surveillance and response. Abuja, Nigeria. 2005. Available from: cheld.org/wp.../National-Policy-on-Integrated-Disease- Surveillance-and-Response.pdf. [Accessed December 12, 2016].
In article      
 
[26]  International Business Machines Corporation. IBM-Statistical Package for the Social Sciences (SPSS) Statistics 20. Somers New York: IBM Corporation; 2011.].
In article      
 
[27]  Blignault I, Ritchie J. Revealing the wood and the trees: Reporting qualitative research. Health Promot J Austr. 2009; 20(2): 140-5.
In article      View Article  PubMed
 
[28]  Kyei-Faried S, Appiah-Denkyira E, Brenya D, Akuamoa-Boateng A, Visser L. The role of community-based surveillance in health outcomes measurement. Ghana Med J. 2006; 40(1): 26-30.
In article      
 
[29]  Stone E, Miller L, Jasperse J, Privette G, Diez-Beltran JC, Jambai A, et al. Community event-based surveillance for Ebola virus disease in Sierra Leone: Implementation of a national-level system during a crisis. PLoS Curr. 2016; 1. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5222551/. [Accessed July 26, 2017].
In article      
 
[30]  Ratnayake R, Crowe SJ, Jasperse J, Privette G, Stone E, Miller L, et al. Assessment of community event-based surveillance for Ebola virus disease, Sierra Leone, 2015. Emerg Infect Dis. 2016; 22(8): 1431-1437.
In article      View Article  PubMed
 
[31]  Okiror SO, Bisrat F, Lutukai M, Bhui BR. Community-based surveillance on polio eradication in the Horn of Africa. African health monitor. 2015; 10: 44-45
In article      
 
[32]  Diaz-Quijano FA, Martínez-Vega RA, Rodriguez-Morales AJ, Rojas-Calero RA, Luna-González ML, Díaz-Quijano RG. Association between the level of education and knowledge, attitudes and practices regarding dengue in the Caribbean region of Colombia. BMC Public Health 2018; 18: 143.
In article      View Article  PubMed
 
[33]  Toda M, Zurovac D, Njeru I, Kareko D, Mwau M, Morita K. Health worker knowledge of Integrated Disease Surveillance and Response standard case definitions: a cross-sectional survey at rural health facilities in Kenya. BMC Public Health 2018; 18: 146.
In article      View Article  PubMed
 
[34]  Sanders D, Lehmann U. Community health workers: What do we know about them? The state of the evidence on programmes, activities, costs and impact on health outcomes of using community health workers. Evidence and Information for Policy 2007. Available from: http://www.who.int/hrh/.../community_health_workers.pdf. [Accessed March 17, 2016].
In article      
 
[35]  Javanparast S, Baum F, Labonte R, Sanders D. Community health workers’ perspectives on their contribution to rural health and well-being in Iran. Am J Public Health. 2011; 101: 2287-92.
In article      View Article  PubMed
 
[36]  Alam K, Tasneem S, Oliveras E. Retention of female volunteer community health workers in Dhaka urban slums: A case-control study. Health Policy Plan. 2012; 27: 477-486.
In article      View Article  PubMed
 
[37]  Patel U, Pharr JR, Ihesiaba C, Oduenyi FU, Hunt AT, Patel D, et al. Ebola Outbreak in Nigeria: Increasing Ebola Knowledge of Volunteer Health Advisors. Glob J Health Sci. 2016; 8(1): 72-78.
In article      View Article  PubMed
 
[38]  Hamisu AW, Johnson TM, Craig K, Mkande P, Banda R, Tegegne SG, et al. Strategies for improving polio surveillance performance in the security-challenged Nigerian states of Adamawa, Borno, and Yobe during 2009-2014. J. Infect. Dis. 2016; 213(3): S136-S139.
In article      View Article  PubMed
 
[39]  Strachan DL, Kallander K, Ten-Asbroek AH, Kirkwood B, Meek S, Lorna B, et al. Interventions to improve motivation and retention of community health workers delivering integrated community case management (iCCM): Stakeholder perceptions and priorities. Am J Trop Med Hyg. 2012; 87(5): 111-9.
In article      View Article  PubMed
 
[40]  Curry D, Bisrat F, Coates E, Altman P. Reaching beyond the health post: Community based surveillance for polio eradication. Dev Pract. 2013; 23(1): 69-78.
In article      View Article
 
[41]  Malaviya P, Picado A, Hasker E, Ostyn B, Kansal S, Pratap R, et al. Health and demographic surveillance system profile: The Muzaffarpur-TMRC health and demographic surveillance system. Int. J. Epidemiol. 2014; 43(5): 1450-1457.
In article      View Article  PubMed
 
[42]  Hyman P. 'Peace technologies' enable eyewitness reporting when disasters strike. Communications of the ACM 2014; 57(1): 27-29.
In article      View Article
 
[43]  Nsubuga P, Brown WG, Groseclose SL, Ahadzie L, Talisuna AO, Mmbuji P, et al. Implementing integrated disease surveillance and response: Four African countries’ experience, 1998-2005. Glob. Public Health. 2010; 5(4): 364-80.
In article      View Article  PubMed
 
[44]  Dil Y, Strachan D, Cairncross S, Korkor AS, Hill Z. Motivations and challenges of community-based surveillance volunteers in the northern region of Ghana. J Community Health. 2012; 37: 1192-98.
In article      View Article  PubMed
 
[45]  Kuijk A. Two factor theory by Frederick Herzberg. 2018. Available from: https://www.toolshero.com/psychology/theories-of-motivation/two-factor-theory-herzberg/. [Accessed October 30, 2018].
In article      
 

Published with license by Science and Education Publishing, Copyright © 2020 Chijioke A Ezenyeaku, Chinomnso C Nnebue, Simeon A Nwabueze, Cyril C Ezenyeaku, Ifeanyi N Udedibia, Ifeoma C Iloghalu and Obiageli F Emelumadu

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Chijioke A Ezenyeaku, Chinomnso C Nnebue, Simeon A Nwabueze, Cyril C Ezenyeaku, Ifeanyi N Udedibia, Ifeoma C Iloghalu, Obiageli F Emelumadu. Completeness of Reporting in the Community-based Disease Surveillance and Notification System in Anambra State, Nigeria. American Journal of Public Health Research. Vol. 8, No. 3, 2020, pp 77-86. http://pubs.sciepub.com/ajphr/8/3/1
MLA Style
Ezenyeaku, Chijioke A, et al. "Completeness of Reporting in the Community-based Disease Surveillance and Notification System in Anambra State, Nigeria." American Journal of Public Health Research 8.3 (2020): 77-86.
APA Style
Ezenyeaku, C. A. , Nnebue, C. C. , Nwabueze, S. A. , Ezenyeaku, C. C. , Udedibia, I. N. , Iloghalu, I. C. , & Emelumadu, O. F. (2020). Completeness of Reporting in the Community-based Disease Surveillance and Notification System in Anambra State, Nigeria. American Journal of Public Health Research, 8(3), 77-86.
Chicago Style
Ezenyeaku, Chijioke A, Chinomnso C Nnebue, Simeon A Nwabueze, Cyril C Ezenyeaku, Ifeanyi N Udedibia, Ifeoma C Iloghalu, and Obiageli F Emelumadu. "Completeness of Reporting in the Community-based Disease Surveillance and Notification System in Anambra State, Nigeria." American Journal of Public Health Research 8, no. 3 (2020): 77-86.
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  • Table 3a. Association between socio-demographic factors and completeness of disease notification among the respondents
  • Table 3b. Association between selected factors and completeness of disease notification among the respondents
  • Table 3c. Association between selected factors and completeness of disease notification among the respondents
  • Table 4. Univariate analysis of factors affecting the completeness of disease case notification among the respondents
  • Table 5. Multivariate analysis of factors affecting the completeness of disease case notification among the respondents
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[13]  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(1): 14-19.
In article      View Article
 
[14]  Nigeria data portal. Nigeria population census. 2006. Available from: https://www.nigeria.opendataforafrica.org/xspplpb/nigeria-census. [Accessed June 8, 2017].
In article      
 
[15]  National bureau of statistics. Nigeria’s population now 193.3 million. 2016. Available from: http://www.nigerianstat.gov.ng/ [Accessed November 12, 2017).
In article      
 
[16]  Anambra State Ministry of Health. Anambra State government strategic health development plan (2010-2015). 2010. Available from: www.mamaye.org/sites/default/files/.../ANAMBRA%20SSHDP%2015012010.pdf. [Accessed August 15, 2016].
In article      
 
[17]  International Federation of Red Cross and Red Crescent Societies. Community-based surveillance - Guiding principles. 2017. Available from: www.cruzrojazika.org/wpcontent/uploads/.../CommunityBasedSurveillance_Global_LR.p..[Accessed October 20, 2017].
In article      
 
[18]  World Health Organization. International Health Regulations (2005). 3rd ed. Geneva: The Organization; 2016. Available from: http://www.who.int/topics/internationalhealth_regulations/en/. [Accessed July 29, 2016].
In article      
 
[19]  Araoye MO. Research methodology with statistics for health and social sciences. 2nd ed. Illorin: Nathadex Publications; 2008. p. 115-22.
In article      
 
[20]  Maes E, Zimicki S. An evaluation of community-based surveillance in the northern region of Ghana. 2000. Available from: http/www.unicef.org/evaldatabase/ index _ 14293.html. [Accessed July 26, 2016].
In article      
 
[21]  Anambra State Ministry of Health - Office of the state Epidemiologist. Community informants profile. 2016. Pg 1- 20.
In article      
 
[22]  Bowler’s proportional allocation formula. In. Pandey R, Verma MR. Samples allocation in different strata for impact evaluation of developmental programme. Rev. Bras. Biom. São Paulo, 2008; 26(4), p.103-112.
In article      
 
[23]  WHO/CDS/CSR/ISR. Protocol for the Assessment of National Communicable Disease Surveillance and Response Systems. 2001. Available from: www.who.int/csr/resources/publications/surveillance/whocdscsrisr20012.pdf. [Accessed January 26, 2017].
In article      
 
[24]  Aniwada EC, Obionu CN. Disease surveillance and notification, knowledge and practice among private and public primary health care workers in Enugu State, Nigeria: A comparative study. Br J Med Med Res. 2016;13(3):1-10.
In article      View Article
 
[25]  Federal Ministry of Health. National policy on integrated disease surveillance and response. Abuja, Nigeria. 2005. Available from: cheld.org/wp.../National-Policy-on-Integrated-Disease- Surveillance-and-Response.pdf. [Accessed December 12, 2016].
In article      
 
[26]  International Business Machines Corporation. IBM-Statistical Package for the Social Sciences (SPSS) Statistics 20. Somers New York: IBM Corporation; 2011.].
In article      
 
[27]  Blignault I, Ritchie J. Revealing the wood and the trees: Reporting qualitative research. Health Promot J Austr. 2009; 20(2): 140-5.
In article      View Article  PubMed
 
[28]  Kyei-Faried S, Appiah-Denkyira E, Brenya D, Akuamoa-Boateng A, Visser L. The role of community-based surveillance in health outcomes measurement. Ghana Med J. 2006; 40(1): 26-30.
In article      
 
[29]  Stone E, Miller L, Jasperse J, Privette G, Diez-Beltran JC, Jambai A, et al. Community event-based surveillance for Ebola virus disease in Sierra Leone: Implementation of a national-level system during a crisis. PLoS Curr. 2016; 1. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5222551/. [Accessed July 26, 2017].
In article      
 
[30]  Ratnayake R, Crowe SJ, Jasperse J, Privette G, Stone E, Miller L, et al. Assessment of community event-based surveillance for Ebola virus disease, Sierra Leone, 2015. Emerg Infect Dis. 2016; 22(8): 1431-1437.
In article      View Article  PubMed
 
[31]  Okiror SO, Bisrat F, Lutukai M, Bhui BR. Community-based surveillance on polio eradication in the Horn of Africa. African health monitor. 2015; 10: 44-45
In article      
 
[32]  Diaz-Quijano FA, Martínez-Vega RA, Rodriguez-Morales AJ, Rojas-Calero RA, Luna-González ML, Díaz-Quijano RG. Association between the level of education and knowledge, attitudes and practices regarding dengue in the Caribbean region of Colombia. BMC Public Health 2018; 18: 143.
In article      View Article  PubMed
 
[33]  Toda M, Zurovac D, Njeru I, Kareko D, Mwau M, Morita K. Health worker knowledge of Integrated Disease Surveillance and Response standard case definitions: a cross-sectional survey at rural health facilities in Kenya. BMC Public Health 2018; 18: 146.
In article      View Article  PubMed
 
[34]  Sanders D, Lehmann U. Community health workers: What do we know about them? The state of the evidence on programmes, activities, costs and impact on health outcomes of using community health workers. Evidence and Information for Policy 2007. Available from: http://www.who.int/hrh/.../community_health_workers.pdf. [Accessed March 17, 2016].
In article      
 
[35]  Javanparast S, Baum F, Labonte R, Sanders D. Community health workers’ perspectives on their contribution to rural health and well-being in Iran. Am J Public Health. 2011; 101: 2287-92.
In article      View Article  PubMed
 
[36]  Alam K, Tasneem S, Oliveras E. Retention of female volunteer community health workers in Dhaka urban slums: A case-control study. Health Policy Plan. 2012; 27: 477-486.
In article      View Article  PubMed
 
[37]  Patel U, Pharr JR, Ihesiaba C, Oduenyi FU, Hunt AT, Patel D, et al. Ebola Outbreak in Nigeria: Increasing Ebola Knowledge of Volunteer Health Advisors. Glob J Health Sci. 2016; 8(1): 72-78.
In article      View Article  PubMed
 
[38]  Hamisu AW, Johnson TM, Craig K, Mkande P, Banda R, Tegegne SG, et al. Strategies for improving polio surveillance performance in the security-challenged Nigerian states of Adamawa, Borno, and Yobe during 2009-2014. J. Infect. Dis. 2016; 213(3): S136-S139.
In article      View Article  PubMed
 
[39]  Strachan DL, Kallander K, Ten-Asbroek AH, Kirkwood B, Meek S, Lorna B, et al. Interventions to improve motivation and retention of community health workers delivering integrated community case management (iCCM): Stakeholder perceptions and priorities. Am J Trop Med Hyg. 2012; 87(5): 111-9.
In article      View Article  PubMed
 
[40]  Curry D, Bisrat F, Coates E, Altman P. Reaching beyond the health post: Community based surveillance for polio eradication. Dev Pract. 2013; 23(1): 69-78.
In article      View Article
 
[41]  Malaviya P, Picado A, Hasker E, Ostyn B, Kansal S, Pratap R, et al. Health and demographic surveillance system profile: The Muzaffarpur-TMRC health and demographic surveillance system. Int. J. Epidemiol. 2014; 43(5): 1450-1457.
In article      View Article  PubMed
 
[42]  Hyman P. 'Peace technologies' enable eyewitness reporting when disasters strike. Communications of the ACM 2014; 57(1): 27-29.
In article      View Article
 
[43]  Nsubuga P, Brown WG, Groseclose SL, Ahadzie L, Talisuna AO, Mmbuji P, et al. Implementing integrated disease surveillance and response: Four African countries’ experience, 1998-2005. Glob. Public Health. 2010; 5(4): 364-80.
In article      View Article  PubMed
 
[44]  Dil Y, Strachan D, Cairncross S, Korkor AS, Hill Z. Motivations and challenges of community-based surveillance volunteers in the northern region of Ghana. J Community Health. 2012; 37: 1192-98.
In article      View Article  PubMed
 
[45]  Kuijk A. Two factor theory by Frederick Herzberg. 2018. Available from: https://www.toolshero.com/psychology/theories-of-motivation/two-factor-theory-herzberg/. [Accessed October 30, 2018].
In article