Identification of disease outbreaks and role of data analysis: An experience from Nadia district in West Bengal - India

 

Roy Bibhas¹, Dan Amitabha², Pasi A R², Jalaluddeen M², Kunal Kanti De³

¹Deputy Assistant Director of Health Services, West Bengal Public Health and Administrative Services

²Airport Health Organisation, Ministry of Health and Family Welfare, Govt. of India, Sahar Approach Road, Andheri (E), Mumbai – 400099

³Deputy CMOH, Howrah, West Bengal Public Health and Administrative Services

 

ABSTRACT:

Introduction: Integrated Disease Surveillance Programme (IDSP) was launched in West Bengal in November 200. Nadia district in West Bengal has a good reporting mechanism under IDSP and data has been computerised since 2007. Present study is analysis of data collected in ‘S’ forms for fever syndrome. Objectives of the study was (1) to describe the suspected cases of fever reported by the district IDSP cell of Nadia, West Bengal during 2010 by time and place (2) to estimate weekly trigger indices for each syndrome and (3) to compare reported outbreak response with estimated outbreaks. Material and Methods: it was a cross sectional descriptive study based on secondary data. The study was conducted in Nadia district of West Bengal from November 2010 to February 2011. The reference period was January 2008 to December 2010. Results: During year 2010, total 3,36,814 fever cases were reported  in Nadia district. Out of total fever cases, 72% (242605 cases) was “Only fever” followed by “Fever with cough and cold” (24.1%, 81101 cases). Conclusion: Fever with cough and cold was increasing in Nadia over last 3 years. Transmission of fever with rash was high in monsoon and post monsoon period. Outbreak response was not data based.

 

 

INTRODUCTION:

In India, many disease surveillance programmes were operating as vertical programmes before 2004. This led to use of different case definitions. In order to streamline the surveillance and reporting of diseases Integrated Disease Surveillance Programme (IDSP) was launched in 2004 in India in a phased manner. It was launched in West Bengal in November 2005 but was operational in year 2006. Initially 13 core disease conditions were brought under surveillance and states were free to add their own priority conditions to it¹. Other objectives of the programme were to expand the surveillance net, build up baseline local indices for expected frequency of disease and respond early to outbreaks when such indices are breached. These indices were called “triggers”. Initially some triggers were specified in the programme with the expectation that with time each state, district and its subunits will build up their own “triggers’ based on reported frequency of disease. The trigger value specified for suspected fever of any type was occurrence of more than 2 similar cases in a village of 1000 population.

 

The IDSP training manual clearly states that data analysis should be done at each level though the district is the nodal agency, triggers or expected frequency of disease should be calculated based on rates in previous years rather than only numbers and proposed the use of graphs for easy visualisation of breach of triggers by disease in the current year. IDSP used 3 types of definitions for each disease condition: Symptomatic definition used by lay people and paramedical staff, probable definition used by Medical officers based on their clinical opinion and L definitions used by labs after confirming the case. The reporting system captured these data separately on S, P and L forms respectively. The District was made the nodal agency for data analysis, feedback and collaboration with the state and the lower units. Outbreak response was expected from Blocks and District whenever detected^1-3.

 

Fever an important syndrome under IDSP captured in S forms under seven categories intended to capture different diseases. Analysing data of fever on the S form could give insight into frequency of the syndromes at local level, describing trends and mechanisms of detecting and responding to outbreaks.

Nadia district of West Bengal is located at the middle of the state. It has 4 subdivisions and 17 blocks. The Tehatta subdivision has Karimpur I, Karimpur II, Tehatta I and Tehatta II blocks, Ranaghat subdivision has Ranaghat I, Ranaghat II, Santipur and Nabadwip (also called Maheshganj) blocks, Kalyani subdivision has Haringhata and Chakdaha blocks and Krishnanagar subdivision has the rest of the 7 blocks. In the district, 18 out of 33 outbreaks reported in 2010 were due to fever. There was a rising trend of Chikungunya and Dengue. The district has a good reporting mechanism under IDSP and data has been computerised since end of 2007. It was decided to analyse the secondary data in S forms for fever syndrome of the district.

 

OBJECTIVES:

Study was conducted with following objectives,

1.       To describe the suspected cases of fever reported by the district IDSP cell of Nadia, West Bengal during 2010 by time and place.

2.       To estimate weekly trigger indices for each syndrome

3.       To compare reported outbreak response with estimated outbreaks.

 

MATERIAL AND METHODS:

Study design:

Cross sectional descriptive study based on secondary data.

Study population:

The entire population of Nadia, West Bengal.

Study period:

The study was conducted from November 2010 to February 2011. The reference period was January 2008 to December 2010.

 

Operational definition:

“Trigger”: Expected incidence rate of the particular category of fever for a particular week for a particular reporting unit computed by mean incidence rate of the previous 2 years. Estimated Outbreak: The number of times in a year the actual incidence rate of a category of fever was significantly more than the “trigger’ values.

 

Reported outbreak:

Outbreaks reported by the lower units to the District and investigated.“S” definitions: Symptomatic definitions of diseases related to fever as defined in IDSP were used for this study. These were a) Only fever ( Malaria, Typhoid) b) Fever with rash ( Measles, Dengue) c) Fever with bleeding( Dengue) d) Fever with cough and cold(ARI) e) Fever with joint pain (Chikungunya) f) Fever with unconsciousness( Japanese Encephalitis, Complicated Malaria) and g) Fever for more than 7 days( Malaria, Typhoid).

 

Data sources and collection:

All IDSP data for the years 2008 to 2010 in S reporting forms and all reported outbreaks data for year 2010 was collected in electronic format from the District Surveillance unit.

 

Data Analysis:

We estimated the incidence rate of total fever cases in Nadia and its Blocks for year 2010. We estimated the proportion of different categories of the fever syndrome to total fever cases and compared them among the 4 subdivisions of Nadia. Time trends of different categories of fever were drawn for the years 2008 to 2010. For denominator, we used projected weekly population assuming uniform weekly growth in the Blocks based on 2001 census. Trigger values were calculated for each fever type for each week for each Block averaging the same week data of the previous two years. Upper limit and lower limit of 95% Confidence interval of the trigger values and the actual weekly incidence rate were plotted on line diagrams for each fever type for Nadia and its Blocks. Outbreaks were detected from the graphs whenever the incidence line crossed the upper limit of Confidence interval line. The return of the former line to the latter was taken as the end point of the outbreak. Number of such outbreaks were estimated Blockwise for each syndrome and compared with reported outbreaks. Mixed outbreaks of diseases covering two syndromes were counted as separate outbreaks. The difference in estimated and reported outbreaks was computed to estimate missed outbreak and determine sensitivity of the system to respond to outbreaks. Negative values for such difference were computed as 0.

 

RESULTS:

Burden of disease: There were total 3,36,814 reported fever cases in Nadia in 2010. Karimpur-I(37928 cases: 11%), Karimpur-II(37928cases,10%) and Nakashipara (33381cases,10%) reported 31% of total fever cases. Annual incidence rate of total fever cases in Nadia was 6.3% in 2010. The distribution in Blocks ranged from 3.5% in Santipur to 19.7% in Karimpur-I. Karimpur II has a high incidence at 15.3 % (Fig-1).

 

Out of total fever cases in Nadia in 2010, the 72% (242605 cases) was “Only fever” followed by “Fever with cough and cold” (24.1%, 81101 cases). ‘Only fever’ was also the predominant fever type in all subdivisions of Nadia comprising 80% of all fevers except in Tehatta subdivision where it was 54%. “Fever with cough and cold” was the next predominant type in all subdivisions. While it was 18% of all fever cases in Krishnanagar and Kalyani subdivisions, it was 14% in Ranaghat and 41% in Tehatta subdivision. All other types of fever contributed to 2% of fever cases in Kalyani and Krishnanagar subdivisions but almost 5 % and 7% in Tehatta and Ranaghat subdivisions respectively (Fig 2).

 

Annual trends:

Annual trends in incidence of total fever in Nadia showed a marginal decline from 6.8% in 2008 to 6.32% in 2010. The trend in Blocks showed an increase in 4 blocks (23.5%), and decrease in 9 blocks (53%). It was constant in the other blocks. While Karimpur I showed a decline in incidence since 2008, Karimpur II showed a rise in fever incidence (Table 1). ‘Fever with cough and cold’ increased in Nadia from 1.2% to 1.5% since 2008. Fever with rash has declined since 2008 to 2010 (Fig 3).

 

 

Table 1: Incidence of reported fever cases in Nadia, West Bengal India 2008-10

Name of the district / Blocks	Incidence of fever cases in percentage
	Year 2008	Year 2009	Year 2010
Nadia district	6.7	6.8	6.3
Krishna Nagar I	3.5	3.4	3.7
Krishna Nagar II	10.7	10.6	9.2
Kaliganj	5.9	6.6	7
Nakashipara	8.6	8.5	8.6
Nabadwip	5.2	6.3	5.1
Krishnaganj	9.3	10.3	6.4
Chapra	7.3	7.4	6.8
Hanskhali	7.3	6.7	6.7
Ranaghat I	5.9	4.2	3.8
Ranaghat II	4.8	4.6	4.8
Santipur	3.7	4.2	3.5
Karimpur II	19.3	19.3	15.3
Karimpur I	17.2	17.7	19.7
Tehatta I	5.6	8.5	5.6
Tehatta II	6.1	6.6	6.7
Chakdaha	4.1	4.3	4.1
Haringhata	4.7	4	4.1

Seasonal trends:

Fever with rash showed a rise in the months of May to July. There was another peak during November December. There was a sudden rise of fever with joint pain since July 2010 in Nadia. During the same period there was a 12% increase in fever cases of this category in Ranaghat. Other fever types showed intermittent peaks but showed no seasonal trends (Fig 3).

 

Outbreak response:

The overall fever incidence and the different types of fever did not increase above 1.96 SD of mean for the year 2010 at Nadia signifying no breach of trigger values. However, weekly indices of different types of fever in different Blocks crossed such trigger values 104 times. 33 outbreaks were reported in Nadia in 2010 by the Blocks, 18 of them due to fever. All the reported outbreaks were investigated and 15 of them laboratory confirmed. Breaking up the reported outbreaks into syndromes and comparing it with the estimated outbreaks from the graphs, there were 92 outbreaks (88% of 104) which were not detected or investigated. 72 out of 92 such outbreaks were missed at KrishnagarI (27), Tehatta II (24) Karimpur I(11) and Chapra(10). 5 of the 17 Blocks (29%) did not report a single outbreak during the year 2010.Some outbreaks were reported by different blocks when the trigger indices were actually not breached on the line diagram (Table 2).

 

 

Table 2: Potential Outbreaks missed in Nadia, West Bengal, 2010

Name of Blocks	Outbreaks Reported by DSU	Outbreaks detected by data analysis	Number of missed outbreaks
Nadia district	18	104	92
Krishna Nagar I	02	29	27
Krishna Nagar II	1	2	3
Kaliganj	1	8	9
Nakashipara	0	0	0
Nabadwip	2	2	0
Krishnaganj	1	1	0
Chapra	0	4	4
Hanskhali	2	8	10
Ranaghat I	0	1	1
Ranaghat II	2	2	0
Santipur	2	2	0
Karimpur II	0	0	0
Karimpur I	2	9	11
Tehatta I	1	1	0
Tehatta II	0	24	24
Chakdaha	1	1	3
Haringhata	1	1	0

 

DISCUSSION:

Fever case detection was less than 10% of population as required by the National Malaria control programme. One-third of fever cases were detected in 3 blocks. Predominant fever type was only fever followed by fever with cough. Overall fever trend of Nadia was declining but it varied in the blocks. Fever with rash showed 2 seasonal peaks at Jan to May and Sept to December.. Fever with cough was increasing. There was a sharp increase of fever with joint pain at the end of 2010.It suddenly rose in the first week of July had a steep hike till September and then started coming down but did not reach baseline till end of 2010.. Block level data analysis showed many missed outbreaks.

 

Total incidence of fever in Nadia slightly decreased but the detection rate was still around 6 % of the population. As per National Anti-malaria Programme guidelines, there was a 4% burden of fever which was not captured also with the most sensitive S reporting forms in IDSP.

 

There was wide variation in the fever incidence in different blocks though the predominant type of fever remained same. The annual incidence was maximum in Karimpur I and II blocks which were both bordering Bangladesh. These blocks were flooded almost every year and there was trans-border migration of population. These two Blocks along with Nakashipara also harbours the highest case load of fever of Nadia. Though the predominant fever type almost all over Nadia was “only fever”, no outbreaks of Malaria or Typhoid, the diseases which this syndrome is supposed to capture under IDSP, was reported in 2010. Most of the outbreaks reported were due to Chikungunya or Dengue or mixed infection. There were many such outbreaks in 2009 which created panic among the people of Nadia. Sensitisation of the health staff to the disease or increased self reporting may be the cause of such detection. Fever with cough and cold was increasing indicating the need for better surveillance of such patients for ARI and TB.

 

The trends indicate that fever with rash peak in the monsoon and post monsoon season .This period coincides with period of increased vector breeding. Active fever surveillance and vector surveillance was needed during this period. There were some ‘silent’ blocks which did not detect any outbreak at all. There could be under-reporting from these blocks. Tehatta I reported only 6 cases of ‘fever with cough and cold” in 2010 which was under reporting.

 

Reported outbreaks were investigated in the district to the point of laboratory confirmation in most cases. This shows good response to reported outbreaks. However there was gap in detection of outbreaks by data analysis. Despite having a computerised data collection system with online web portal entry, data is analysed only for numbers and not converted into rates. The trigger indices were also not calculated for whatever data was available for the previous years. Therefore, there was no clarity on the expected frequencies during the current period and when to call the occurrence an outbreak and respond to it. This was further evident from the fact that some outbreaks were reported when the frequency of disease did not cross the expected frequency. The responses were more perceptual than based on actual data. Thus the system was not alert enough to adequately respond to outbreaks. The sensitivity of outbreak response was only 13%.

 

The results also highlight the need for data analysis at the sub-district level as the data gets diluted as it moves up the reporting ladder. This was envisaged in the IDSP training manual also. In this study, none of the fevers showed any breach of trigger value in Nadia but there were many breaches when the data was analysed for Blocks for different fever types.

 

LIMITATION:

Person analysis could not be done as the data was not tabulated in the electronic format available in the district. Tabulation from paper format could not be done due to volume of the data and time constraints. IDSP data is available for only <5 and >5 age groups stratified by sex.

CONCLUSION:

Fever with cough and cold was increasing in Nadia over the last 3 years. There was high fever incidence in Karimpur I, Karimpur II and Nakashipara. Transmission of fever with rash was high in monsoon and post monsoon period. Outbreak response is not data based. There is no clarity about expected frequency of fever by the sub-district units. Analysis at district level is based on numbers and not rates.

 

RECOMMENDATIONS:

1.       RNTCP programme and ARI control should be strengthened.

2.       Mass survey in Karimpur I, II and Nakashipara to find out reasons for high transmission.

3.       Entomological survey of the area, IEC and source reduction activities to be geared up in premonsoon period.Active surveillance with confirmation of each “only fever” cases with RDK or slide collection to rule out malaria.

4.       Distribution of impregnated bed nets in priority Blocks.

5.       Data analysis should be done on the basis of rates instead of absolute numbers to adjust for population.

6.       Analysis of data at sub-district level to be done as outbreaks are missed due to pooling of data at the district. Capacity building of the sub-district tier could generate prompt outbreak response.

7.       Prompt data analysis to detect when fever is crossing the trigger value. The methodology used here can be used as a tool as all BPHCs have computers and data entry operators. The entry of fever frequency will auto generate the graph which can be used as a tool for instant action.

 

REFERENCES:

1.        Government of India. Medical Officers Manual. Integrated Disease surveillance Project. New Delhi. 2005.

2.        Government of India. IDSP Training manual for State and District Surveillance Officers. New Delhi. 2005. http://idsp.nic.in/old/nicd/IDSP_DSO_Sept08/Resources_files/DistrictSur  vMan/Module5.pdf

3.        A complete Reference for Data Managers and Data Entry Operators in IDSP. Available from url: http://idsp.nic.in/idsp/UserManaula/ModuleA.pdf.

 

 

Received on 21.01.2016          Modified on 29.01.2016

Accepted on 20.03.2016         © A&V Publication all right reserved