1 Introduction

Dengue is the most important mosquito-borne viral disease and its history was gone back to in Dynasty of 265-420 AD. The virus and its vectors have now become widely distributed throughout tropical and subtropical regions of the world, particularly over the last half century (Eisen and Lozano-Fuentes, 2000). The World Health Organization estimates that more than 2.5 billion people are at risk of dengue infection. First recognized in the 1950s, it has become a leading cause of child mortality in several Asian and South American countries. Population growth, increased urbanization, international travel, and climate changes are the affecting factors for the emergence and re-emergence of dengue fever in different parts of the world (Geneva, WHO, 1997). When its control and prevention strategies used so far in many outbreak situations in different parts of tropical and subtropical countries, it has been well documented that the effective vector control yielded desirable results (Eisen and Lozano-Fuentes, 2000; Fooks et al., 2000). Ravelling the strategic plan for the prevention and control of dengue fever in which a few of the following had been highlighted (1) Surveillance for planning and response (2) Disease management (3) Emergency preparedness (4) Changing behaviours and building partnerships and (5) Capacity building (SCVBD, 2005). In these strategic plans, the role of clinicians, updating of clinical guidelines for early diagnosis and management of dengue fever, emergency activities on case detection and investigation, emergency vector control, mobilization of various sectors of the community in a sustained program in dengue fever prevention and control and build up surge capacity by providing training on clinical epidemiological aspects of dengue fever and its public health management have been included. Even though, experiences gained from the implementation of dengue strategic plans in India especially in several outbreaks of Tamil nadu, still it has properties to be tuned in the following aspects are (1) impacts or practical difficulties on the convergence of daily fever cases from all resources, (2) rapid entomological surveillance with reference to Premises condition index (PCI) (3) the role of entomological indices, House Index(HI), Breteau Index (BI) and their threshold levels to stop dengue outbreak (4) role of laboratory confirmation on dengue both by the Ig-M, Ig-G and NS1of both ELISA and card tests (5) variations in involvement among workers and supervisors in dengue control activities (6) factors that affecting the cause of dengue fever (7) vital needs of community participation (8) impact on Information Education and Communication (IEC) (9) clinical managements in Hospitals (10) time taken to control the outbreak with reference to the incubation of dengue virus and the circulation of more than one type of Dengue viruses and its significance (Basker and Ezhil, 2012; Basker et al., 2013; Basker and Kolandaswamy, 2015).

The present study has been dealt the evaluation of the dengue outbreak situation with reference to Aedes indices in Rajapalayam municipality of Tamil Nadu, India which had an outbreak in December 2014 and ended in February 2015. The importance of basic steps of epidemiology in the outbreak, role of indices HI and BI and its threshold that took part in stopping the outbreak, attributes on involvement among workers and supervisors while engaging in vector control activities and the role of indices in halting the outbreak within one incubation of dengue virus in human have been ascertained. Since these elements had been a great role in stopping dengue in several outbreaks of Tamil Nadu, India, this study has been received more attention for not only to assess the role of indices those are imperative to evaluate the dengue control programme but also with the intention of including these findings in the universal dengue control strategic plans combining with the specific factors prevailing in a place of the outbreak.

2 Materials and Methods

The study was carried out in Rajapalayam. It is situated in Virudhunagar District of Tamil Nadu, India (Longitude 77^°55’E; Latitude 9^°45’N) with the population of 142 000. Residents of this town are living in 42 wards (small administrative divisions) (Figure 1). This study was undertaken in December 2014 to February 2015 based on confirmed dengue cases were reported. Following it, clinical, entomological and community based control measures had been instituted in wards where Ig-M confirmed cases were being reported from Government Hospital, sentinel tertiary care Hospitals and private clinics. Entomological surveillance was monitoring through the source reduction and chemical control over larval and adult density of Aedes species. Besides, health education had been imparted to the community and schools with prime messages on the setbacks in dengue control such as, non-availability of specific drugs, trans ovarian transmission and the property of the eggs of Aedes that withstand without desiccation more than a year (Mazia et al., 2009).

The data on larval collections from households were recorded in the pre- designed survey forms to arrive different indices namely, House index (HI), Container Index (CI) and Breteau Index (BI). The larval identification was done by using the taxonomic key (WHO, 2013) and its wriggling movements in aquatic habitat. Similarly, the adult collection was made in both dusk (3-6PM) and dawn (8-11AM) periodically and their densities were expressed in 10 Man Hour Density (10 MHD).

To understand the magnitude of the problem, each ward of this urban was stratified based on the following criteria (1) wards of deaths occurred and more than five Ig-M positive cases (2) wards with three to five cases of Ig-M (3) Wards contributed three cases and less than five cases (4) wards with only two cases (5) wards those had reported only one case and (6) wards contributed none of case during the outbreak (Table 1).

A door to door cross sectional entomological survey was carried out in houses where Ig-M positive cases reported and their peri-domestic areas up to 200-300 meters to study the degree of ward wise infestation and it is expressed in terms of HI, CI and BI. These data were taken to analyse for studying the impact of the present strategy with reference to declining trends of cases within one incubation period of time (3-14 days) (Lam, 1993). Entomological survey was done by the Domestic Breeding Checkers (DBC) who searched for Aedes breeding in house to house after hands on training under the supervision of Sanitary Inspector (SI). Further, it was re-checked randomly minimum 25 houses by the Junior Entomologist (JE) and Senior Entomologist (SE). Aedes Indices HI, CI and BI made by DBCs were compared with the indices those had obtained by cross checking of SI, JE and SE was analysed with chi-square using the trail version of SPSS IBM Company, Chicago-3, USA to find out statistically significant level.

3 Results

Since the epidemic control had been prolonged even after one incubation period of dengue (3-14 days), the basic epidemiological stratification was re ascertained based on the criteria arrived already from the outbreak so as able to visualize the lacunae in anti-larval work and thus a new stratifications were delimited as follows (1) four wards (28, 32, 39, and 40) are intersecting both deaths and contributing more than five cases. Likewise, three wards (10, 17 and 30) are intersecting both 3 and less than 5 cases and one ward (26) is in the stratification of the both the death with two cases alone. Thus, wards 10, 17, 26, 28, 30, 32, 34, 35, 39 and 40 were identified as the most vulnerable of all total 42 wards. From this, it was identified that some of wards had to be required intensive anti-larval work with reference to statistically significant and not significant status of indices among DBCs, JE and SE (Table 2; Table 3; Table 4; Table 5; Table 6; Table 7; Table 8; Table 9; Table 10; Table 11).

Further, from this study, it has also been known that indices of entomological surveillance are more reliable to study the impact of interventions made against the dengue during the epidemic situation with time bound (i.e., one incubation period of dengue 3-14 days). Hence, HI, CI and BI those had been collected in all 42 wards in 15 days from the day of intervention were taken to evaluate the impact of anti-larval work. Strata wise computation of HI, CI and BI by the DBCs, under the supervision of Sanitary Inspectors (SI), Junior Entomologist (JE) and Senior Entomologist (SE) had been taken for statistical analysis (Table 12).

Since this epidemic had been extended more than four spells of incubation from the day of the first intervention, anti-larval work was conducted from 29.01.2015 to 11.02.2015 and its follow-up till November 2015 were observed. Data collected by DBCs, Junior Entomologist (JE) and Senior Entomologist (SE) had been analysed to find out significant level and found that some were not statistically significant and some others are significant (Table 13; Table 14; Table 15; Table 16; Table 17).

3.1 Stratum wise statistical analysis

When the statistical analysis was made with Chi-square test between the outcome of anti-larval works of DBCs, junior Entomologist and Senior Entomologist in the first stratum under the criteria, death cum >5 Ig-M positives, it was found statistically significant (p=0.005) and hence sporadic cases of dengue had been reported even after  four span of incubation. It was rectified within one span of incubation as most of sources reduced already so as able to bring into desired threshold of HI and BI with intensive anti larval work and it was found statistically both are significant (Table 13). From these observations, it could be inferred that the variation among DBCs work probably performed under ineffective supervision and it was lead to delayed dengue control along with geographic and socio economic factors.

Observation made in the stratum designated as 3-5 Ig-M dengue confirmed cases revealed that HI and BI found statistically significant (Table 14).

In the stratum which contributes only two cases found statistically not significant. The same observations were also made in both the strata those contributed only one Ig-M confirmed case and none of cases contributed since the onset of the outbreak (Table 15; Table 16; Table 17). These results had been affirmed that there were no positive cases reported when the involvement in anti-larval works of DBCs and all tiers of effective supervision was not significant provided with the threshold level of indices reached whereas sporadic cases had been reported in strata where indices found statistically significant.

Amalgamating all these results, it has been known that minimum 15 days (one incubation of dengue viruses in human is 3-14 days) should be required to halt the outbreak from the day of intervention made despite DBCs involvement in anti-larval work so as able to make in to permissible level and the same had acquired by supervision. In that situation, the entire municipal areas in 42 wards had been divided into six blocks so as able to complete once in a week to avoid the adult emergence and for sustainable anti-larval management for ever (Table 18). In its evident, six days block has been continuing in the municipal area of Rajapalayam since March to till date (December 2015) yielded no Ig-M positive cases (Table 19).

The number of container searched by the three teams irrespective of the number of cases in cluster had significantly high correlation with number of positive container identified (Table 20). Hence, it may be concluded that search of a higher number of containers will increase the detection of positive sources and thus helps to control the spread.

4 Discussions

Dengue is one of the major public health problems almost in all parts of the world. Since there is no vaccine available against the disease, vector control against the Aedes mosquitoes is given emphasis in the dengue control programme (Cheong, 1967). The two vector mosquito species responsible for the transmission of dengue in Rajapalayam municipality is Aedes aegypti and Aedes albopictus. They breed in artificial and natural containers and receptacles which hold clean and clear water in general (Lee and Cheong, 1987; Cheong, 1986). It is known that Ae.aegypti exploits a wide variety of containers that are found in domestic habitats as larval development sites, including containers ranging in size from bottles and cans to large water storage tanks (Jakob and Bebier, 1969). The value of using data from immature to assess spatial patterns of dengue risk has been brought into question. Although some studies have been reported that larval indices are predictive of spatial risk for dengue virus transmission (Reiter et al., 1997; Scott et al., 2004; Lizet et al., 2016). Earthen pots, flower pots, plastic barrels, concrete tanks, coconut shells and discarded tyres are some of the preferential breeding sites in Rajapalayam municipality. Probing strategies so far employed in dengue control, the HI and BI has a great role in outbreaks as these are associated directly with anti-larval measures. For larval control, the activities carried out are source reduction measures, use of Abate or Temephos 50% EC (Emulsified concentration) larvicide, regular house inspection and enforcement of laws etc. (Jakob and Bebier, 1969). It has also been known that HI and BI were useful indicators in the past to assess risk of dengue outbreak and recent studies have indicated that dengue continues to be occurred despite very low larval populations (Guzman and Kouri, 2002; Lizet et al., 2016). Since the threshold of HI, BI have been fluctuating in halting the outbreak, various studies in association of these indices to ovitraps, monitoring the density of adult vector mosquitoes and to block dengue virus replication in mosquitoes with Wolbachia pipientis have been undertaken in order to determine their threshold (Fooks et al., 2000; Gazman and Kouri, 2002; Scott et al., 2004; Lizet et al., 2016) 19 and dengue prevention.

Maps are the foremost tool in any epidemic, to represent the affected units like village, streets or wards to understand the risk at a glance. Now Geographical Information System (GIS) software is becoming more user friendly for this purpose. Besides, this will enable control programs for example, generate risk maps for exposure to dengue virus, develop priority area classifications for vector control and explore socio economic associations with dengue risk (Geneva, WHO 1997; Chadee et al., 1998; Teng, 2001; Sanchez et al., 2006; Moreno et al., 2006; Lozano-Fuentes et al., 2008; Eisen and Eisen, 2008; Aviles et al., 2008).

From the present study, it is derived that the stratification during the outbreak is the foremost tool of epidemiology and it is so important to implement appropriate intervention based on degree of vulnerability. Similar observation was also made in a case control study undertaken in the municipality Playa, Havana (Lozano-Fuentes et al., 2008) in which 50 houses were delimited as blocks and their neighbourhood around 100 meters so as able to evaluate the outbreak with threshold of HI and BI arrived there before, during and after the outbreak.

To strengthen the findings obtained from this research paper that the incubation of dengue serovars in human i.e. 3-14 days are required for halting the outbreak. Similar observation was also made by some researchers (Sanchez et al., 2006; Lozano-Fuentes et al., 2008; Eisen and Eisen, 2008). Further, from this aspect, it has also been inferred that the time taken to halt the outbreak is coincided to an incubation of dengue virus from the day of intervention along with the threshold level of HI and BI arrived after the source reduction of immature stages of Aedes (Jakob and Bebier, 1969; Eisen and Eisen, 2008) and adult control. The above said information is useful to ascertain the minimum time requirement as 15 days (based on the incubation of viruses in human 3-14 days) and if it is extended apart, it could be understood that there are some lacunae in intervention as the existence of hidden habitats of Aedes and there was significant in anti-larval works engaged by DBCs and supervisors.

On the determination of threshold of Aedes indices, HI and BI in the epidemic situation, various schools of thoughts have been prevailed as mere reduction of these indices has not been taken part to halt the outbreak and as many as initiatives have been taken to solve it too. Among initiatives, it was studied extensively particularly on the role of HI and BI before, during and after the dengue outbreak in the municipality Playa of Havana by Sanchez et al. (2006) and Lozano-Fuentes et al. (2008). In his studies, first he computed HI and BI as a whole of municipality with reference to spatial (34.90 km²) and the population (182 485) of the municipality. Its value of HI before, during and after the epidemic was 0.87%, 1.53% and 0.69% respectively. Likewise BI was 0.92, 1.73 and 0.73. Secondly, the municipality was stratified as blocks with cases and without cases. The value of HI before, during and after in the block with cases were 0.92%, 1.97% and 0.48% in 2.85 km² in 21 815 population and BI were 0.99, 2.34 and 0.50 similar delimitation and computation was made to arrive HI and BI in the neighbourhood area of the municipality also. From these results, it was understood that BI in particular, allow identification of geographic units at high risk for dengue transmission. However, in regions with low Ae.aegypti density, identifying such units requires analysis at different levels, i.e. for blocks and neighbourhoods, and short intervals between inspection cycles. Thus the optimal or threshold cut off values of HI and BI have been arrived (Lozano-Fuentes et al., 2008).

Now, the threshold of HI and BI was determined stratum wise during and after the epidemic with reference to the stratum which had no cases at all. It is interesting to note that the average of highest HI (9.8%) and BI (18.3) was at the beginning of the outbreak in the stratum (wards 1, 4, 6, 7, 16, 19, and 23) which did not contribute dengue positive cases as houses are situated sparse, number of less water hold containers are some of reasons along with geographic and socio economic factors. The average indices HI and BI in the stratum which claimed deaths were 6.3% and 10.8 in the stratum of>5 cases, HI and BI was 8.96% and 13.86; in the stratum of three cases and<5 had 8.2% HI and BI 12.7; in the stratum of two and a death had 12% HI and 18 BI and the HI and BI in the strata which had only one case was 5.65% and 9.3 respectively. Indices HI and BI of all strata with cases had become to 4.2% and 5.2 in strata, with death and cases, whereas 0% HI and BI noticed in the stratum which did not have cases when the outbreak had been halted. From these findings, the threshold of HI and BI are around 4% and 5 in areas of cases however both HI and BI had become Zero in their neighbourhood (Table 21).

As the inference of this research paper, the stratification or delimitation is the prime step in epidemic, the minimum time requirement is 15 days for halting the outbreaks, the extension of 15 days lead to probe habitats of Aedes further along with efforts, to make into “not significant”, level over involvement among workers and cross checking agencies (JE, SE) during the epidemic comprising specific threshold of indices HI and BI. Besides, the risk of dengue outbreaks is influenced not only by abundance of Ae.aegypti females, but also by dengue virus serotype specific herd immunity (against dengue virus serotypes 1-4) among the human population (Chadee et al., 1998; Lozano-Fuentes et al., 2008; Morrison et al., 2008; Scott et al., 2008; Thammapalo et al., 2008; Sivagnaname et al., 2012). Still, in depth studies on threshold of Aedes indices are the most urgent need.

Limitations

This research paper excluded the ovitrap indices, adult indices and efficiency of aerial bio-assay to determine their threshold with reference to immature of Aedes indices HI and BI. Hence further intensive studies ahead comprise these excluding factors (Fay and Ferry, 1965; Fay and Eliason, 1966; Hoffman and Killingsworth, 1967; Kilpatrick et al., 1970; Scott et al., 2000; Reiter and Nathan, 2001; Scott and Morrison, 2010).

Conflicts of interest

The authors declare no conflicts of interest.

Acknowledgements

Authors are thankful to all municipal staffs and Sanitary Officer Mr.P.Elango, engaged in anti-larval and anti-adult measures during the epidemic. We thank Junior Entomologist Mr.M.Moorthy, Lab Technicians Mr.R.Anandhan and Mr.S.Dhanasekaran, Driver Mr.A.Mohanraj and Typist Mr.S.Sasikumar of ZET, Cuddalore for their helps during the survey. Further, Mr.M.Kannan, Senior Entomologist, Zonal Entomological Team, Virudhunagar and Junior Entomologists Mr.A.Radhakrishnan, Mr. A.Veeriahan, DDHS’ office, Virudhunagar District are remained for their immense helps in both field inspection and to collect data to bring out this research paper. Above all, we are very grateful for the encouragements and esteemed helps rendered by the District Collector, Mr. V. Rajaram, I.A.S., and then Municipal Commissioner, Mrs. N. Vimala, Virudhunagar District, during this outbreak.

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