Background

Nigeria contributes significantly to global malaria cases and deaths. About 29% of the global malaria cases and 26% of total malaria deaths occur in Nigeria (WHO, 2016). With an estimated population of 160 million and a parasite prevalence of 42% among children with zonal variations ranging from 27.6% in the South-east to 50.3% in the South-west zone, the country still has a large population at risk (National Malaria Strategic Plan, 2014-2020).

Malaria control efforts in Nigeria include the Management of Malaria Cases and the reduction of mosquito population through Integrated Vector Management (IVM). Much of the efforts made towards IVM are geared towards the distribution and use of Long Lasting Insecticide treated Nets (LLINs), scale up of Indoor Residual Spray (IRS) and larval source management (National Malaria Strategic Plan, 2014-2020). Indeed, the gains of these control interventions have not been significant due to challenges of resistance to insecticides in the primary vector Anopheles. However, the malaria vectors in Nigeria have developed resistance to all the four classes of insecticides, much of which have occurred with DDT (Oduola et al., 2010; 2012) and pyrethroids (Awolola et al., 2003; Kristan et al., 2003; Adeogun et al., 2012; PMI, 2015). The phenomenon of physiological resistance to insecticides in the primary malaria vector, Anopheles gambiae, was first observed in Northern Nigeria by Elliot and Ramakrishna in 1956 to the insecticide dieldrin. Within a decade, resistance to Dieldrin had spread to other parts of the country (Elliot and Armstrong, 1956) even to areas without programmatic interventions (Service, 1964). Resistance to DDT was subsequently reported by Prasittisuk and Curtis in 1982. Today, despite the restricted use of DDT in malaria vector control in Nigeria, the vector remained resistant to the insecticide in some parts of the country (Oduola et al., 2010).

Of all the insecticide classes used for malaria vector control, pyrethroids are recommended for the treatment of LLINs while some of these pyrethroid insecticides are also used in IRS. With a large coverage, LLINs and/or IRS interventions can result in dramatic reduction in malaria morbidity and mortality (Lengeler, 2004; Pluess et al., 2010). Nigeria is currently scaling up the distribution of LLINs and the coverage of IRS. In 2008, the overall ITN coverage was 8% but reached 42% in 2010 (USAID/PMI/CDC, 2011) with a steady distribution and utilization to achieve the projected Elimination Status (National Malaria Strategic Plan, 2014-2020). Moreover, long-standing massive use of nets can select resistant populations of mosquitoes and subsequently impart on the success of interventions (Yadouleton, 2010). This makes it pertinent to increase vector surveillance and monitor the development of resistance in the malaria vectors. The current LLIN replacement campaign, coupled with the need to provide sufficient data on the resistance of Anopheles mosquitoes to insecticides in Nigeria prompted this study to determine the resistance status of the major malaria vector Anopheles gambiae mosquitoes to DDT and Deltamethrin insecticides.

1 Materials and Method

1.1 Study localities and mosquito collection

The study was carried out in Oyo state (8°00′N and latitude 4°00′E) in South West Nigeria, with its capital at Ibadan. The state covers approximately an area of 28,454 square kilometers and is ranked 14th by size. The Climate is equatorial, notably with dry and wet seasons with relatively high humidity. The dry season lasts from November to March while the wet season starts from April and ends in October. Average daily temperature ranges between 25°C (77.0°F) and 35°C (95.0°F), almost throughout the year. Agriculture is the main occupation of the people of Oyo State. The climate favour the cultivation of crops like maize, yam, cassava, millet, rice, plantain, cocoa and palm produce with puddles of water available for mosquito breeding sites. Larval samples of mosquitoes were collected from footprints, ponds, pool, puddle and tire tracts, from Urban communities in Oluyole (7^o21.404’N, 3^o50.598’E), Bodija (7^o25.901’N, 3^o54.815’E), Ojoo (7^o27.812’N, 3^o55.017’E), Iwo road (7^o24.042’N, 3^o56.496’E), Eruwa (7^o31.894’N, 3^o25.077’E) and Oyo town (7^o49.923’N, 3^o55.727’E) covering the three senatorial districts Oyo state, between June and November, 2010 using  standard procedures (Service, 1971). The larval and pupal samples were transferred into collection bottles, suitably labelled and reared to adults in the insectary at the Molecular Entomology and Vector Control Unit, Public Health Division, Nigerian Institute of Medical Research, Lagos, Nigeria. Oluyole and Bodija field sites are urban, mainly residential with few industries and petty traders. Ojoo and Iwo road sites are also urban but with large numbers of motor mechanics with relatively moderate amount of oils usually washed from vehicles into surrounding breeding sites. Oyo town and Eruwa are urban and semi-urban respectively with agriculture being the main occupation of the inhabitant. However, no extensive IRS intervention has been conducted in any of the localities but LLINs were distributed in 2012- 2013 and the state is had just replaced the nets in 2016.

1.2 Insecticide susceptibility tests

Insecticide susceptibility tests were carried out by exposing 3-5 day old female adult mosquitoes to 4% DDT and 0.05% Deltamethrin respectively, using the WHO standard protocol (WHO, 1998; 2013). Except in Oluyole study area, a minimum of four replicates of 25 mosquitoes per tube were exposed to the insecticides. Controls include 20-25 mosquitoes per tube in two replicates. Knock down was recorded at an interval of 10minutes for one hour. All test mosquitoes were transferred to holding tubes and provided with cotton pads soaked with a 10% sucrose solution. Final mortality was recorded 24 hours post exposure. Survivors and dead mosquitoes were thereafter preserved separately on silica gel.

1.3 Morphological and PCR identification of samples

All the samples exposed to DDT and Deltamethrin were morphologically identified using the Gilles and Coetzee, 1987, morphological identification guide. DNA was extracted from the samples with the aid of a genomic DNA extraction kit prepGEM^TM insect (ZyGEM Corporation Limited, New Zealand), according to manufacturer’s instructions. The extracted DNA samples were stored in a -20^oC freezer further identified by PCR. Subsequently, 1µl of the DNA extract from each sample was used as template for PCR (Scott et al., 1993). Products of the samples identified as Anopheles gambiae s.s. were further digested with Hha I enzyme to separate between An. gambiae s.s and An. coluzzi species (Fanello et al., 2002).

1.4 Statistical analysis

Habitat type preference and distribution of the mosquitoes collected during the survey was examined using chi-square. Percentage knock down at 10 minutes interval for the 60 minutes knock down exposure period was also calculated with KDT₅₀ and KDT₉₅ values derived per locality and insecticide using probit regression analysis. The final percentage mortality was calculated as a proportion of the mosquitoes that died out of the total population exposed after 24 hours with 95% confidence interval. Correction with Abbots formula was not necessary as the mortality in all the controls were below 5%. Resistance status was determined as laid down by the WHO criteria (WHO, 2013: observed mortality between 98-100% indicates susceptibility, mortality between 90-97% suggests the presence of resistance genes within the population which requires further confirmation and mortality values below 90% confirms resistance to the insecticide examined with the population).

2 Results

2.1 Collection of mosquitoes and larval preference of Anophelines

A total of 58 mosquito larval habitats were sampled from the six localities surveyed (Table 1). Anopheline larvae were found in 33 habitats out of which 12 (20.7%) had anophelines only. Culicine larvae were found in 46 sites and 21 (36.2%) of these habitats had Culicines only. Anophelines and Culicnes cohabit in 25 (43.1%), suggesting that Anophelines and Culicines coexist in majority of the habitats (Table 1). The habitat type distribution for the habitats with Anopheline only or Culicine only larvae was not different (Table 1: χ² = 5.25, degree of freedom [df] = 5, P> 0.01).

2.2 Susceptibility of Anophelines to DDT and deltamethrin insecticides

Overall, 1,210 female Anopheles gambiae s.l. were exposed to DDT and Deltamethrin insecticides. Of these, 610 and 600 were exposed to DDT and Deltamethrin insecticides respectively (Table 2). The knock down rates and mortality values are presented in Table 2 and Figure 1. The mortality rate from exposures to DDT (4%) was 13%, 52%, 82%, 84%, 60% and 30% in Oluyole, Bodija, Ojoo, Iwo road, Eruwa and Oyo town respectively, suggesting high resistance to this organochlorate insecticide DDT. Also, a KDT₅₀ (35.89-472.43) and KDT_{95 (}63.84-6075.11) value indicate low sensitivity to DDT. The susceptibility of the Anopheles gambiae s.l. varied between insecticides. With Deltamethrin, percentage mortality values ranged between 80-100%. The insecticide killed 98% and 100% of the mosquitoes exposed at Oyo town and Iwo road respectively, suggesting susceptibility. However, the sensitivity decreased to 90% and 95% in Ojoo and Eruwa populations respectively, which suggests reduced susceptibility that required further confirmation. Resistance was confirmed at Bodija and Oluyole where the mosquito populations had 80% and 88% mortalities values respectively (Figure 1). The one hour knock down values to deltamethrin was also high across the localities (Table 2). Moreover, it was only the Oluyole populations that had the lowest mortality rate of 13% and lowest knock down profile of 88% which suggests low sensitivity in the population.

2.3 Morphological and Molecular identification of mosquito samples

A total of 1,770, comprising of the exposed samples and controls, were morphologically identified as members of the Anopheles gambiae s.l.. Out of the 1,770 Anopheles gambiae s.l. mosquitoes that were tested through PCR and enzyme digest, six could not be identified even after three runs. Across all localities, Anopheles arabiensis was the dominant species, constituting 1,034 (58.6%) followed by Anopheles coluzzi, 639 (36.2%) and Anopheles gambiae s.s., 91 (5.2%) (Table 3). All the mosquitoes successfully identified at Ojoo were Anopheles arabiensis indicating species dominance (Table 3). Both Anopheles coluzzi and Anopheles arabiensis were found in Oluyole, Iwo road and Bodija respectively. However, Anopheles coluzzi, Anopheles arabiensis and Anopheles gambiae s.s. were found in Oyo town and Eruwa which suggests the sympatric occurrence of the former M and S molecular forms at these sites (Figure 2).

3 Discussions

This study provides a basic information on the larval habitat preference of Anophelines in Urban communities in Oyo State. Spatial heterogeniety was observed in the distribution of Anopheline larval habitats across all localities in this study. However, this study did not identify the possible environmental variables that determine anopheline occurrence and abundance in relation to larval habitats. This is because the spatial heterogeneity in An. gambiae species composition has been reported to be affected either by many variables, each of which has a small effect, or by other important variables that have not yet been measured under field conditions (Robert et al., 1998; Minakawa et al., 1999). Although, this study did not examine the influence of environmental variables on larval site preference, it seem Anophelines and Cilucines primarily breed and coexist freely in most of the habitats examined as this study. Also, this did not detect any statistically significant associations between breeding site preference and mosquito occurrence and abundance.

The susceptibility status of Anopheles mosquitoes to DDT has not been widely studied in Oyo State.  The data available on the resistance of these primary malaria vectors is focal (Awolola et al., 2007) which therefore suggest a dearth need for widespread studies on DDT resistance in the state. Our study hence provide a widespread data on the resistance status of Anopheles mosquitoes to DDT in Oyo State. The mosquitoes showed reduced susceptibility to DDT (13% - 84% mortality) as compared with previous studies (Awolola et al., 2007: 71-82% mortality at Alakia). This indicate reduced sensitivity of the mosquito populations to DDT in the Oyo state. No data has been provided on the resistance status of Anopheles mosquitoes to DDT at Oluyole, Iwo road, Eruwa and Oyo town, prior to this work. Therefore this study provide the first of such data. Data on the high resistance of Anopheles populations to DDT in Oluyole (13% mortality) and Oyo town (30% mortality) affirm the presence of some inherent factors that drives resistance in these localities. Oil spillage has been proven to perform a significant role in the selection of resistant populations in Oyo state (Djouaka et al., 2007), however, Oluyole is an urban area in Ibadan and Oyo town is known for some level of agricultural practices. Factors responsible for the selection of resistant populations at Oluyole and Oyo town is not known. A major contributory factor may be the illegal and uncontrolled use of pesticides including DDT in both Urban centres (Akhiwu and Aligbe, 2000; Oduola et al., 2010) and agriculture (Diabate et al., 2002) in Oyo state (Pesticide Action Network, Nigeria, 2007). However, this is still a mere speculation and would require further studies.

One of the major malaria vector control intervention in Nigeria is the distribution and use of LLIN (National Malaria Strategic Plan, 2014-2020). The LLINs are impregnated with mainly pyrethroids (WHO, 2010) and the massive use of these nets have been reported to select resistant populations in Anopheles gambiae and Anopheles funestus (Etang et al., 2003; Corbel et al., 2004). The data from our study sites (80%-100% mortality) indicate that resistance to pyrethroid is ongoing in Oyo State which could be, in part, as a result of the use of LLIN. This may have negative implication on the success of the intervention in the State. The mortality values recorded for Bodija (88% mortality) and Ojoo (90% mortality) populations in this study indicate ongoing selection at both sites.

Chandre et al. (1999) suggested that high KDT₅₀ values are suggestive of kdr mutations in populations. The comparably low KDT₅₀ values recorded in our study suggest the presence of other mechanisms of resistance in the populations. Although, we did not perform any studies on the frequency of this mutation in our study localities, reports previously published from Oyo State indicate that the kdr mutation is present at a frequency of 0% (Djouaka et al., 2007: Djouaka et al., 2008) to 48.1% (Awolola et al., 2005; Awolola et al., 2007). However, the relatively low frequency of this mutation in certain areas of Oyo State is suggestive of the involvement of metabolic mechanisms of resistance (Brooke et al., 1999; Awolola et al., 2003; Oduola et al., 2010).

The success of any malaria control intervention, either by LLIN or IRS is hinged on the understanding of vector dynamics which in turn depends on the identification of the malaria vectors involved. Although, the distribution of malaria vectors, Anopheles gambiae s.l., has been well documented in Africa (Gillies and Coetzee, 1987; Minakawa et al., 1999; Coetzee et al., 2000), much information is still required for Nigeria. Our study revealed that Anopheles coluzzi, Anopheles arabiensis and Anopheles gambiae s.s. are the three species present in the six localities surveyed. Studies had indicated that these three species are widely distributed throughout Nigeria at varying frequencies across geopolitical zones (Onyabe and Conn, 2001; Onyabe et al., 2003; Awolola et al., 2005; PMI, 2015). This scenario also played out between our sample sites. Anopheles arabiensis was the only species found in Ojoo which is in contrast with earlier report from this site where Anopheles gambiae (S form), now Anopheles gambiae s.s., was the dominant species (Djouaka et al., 2007). The disparity between our data and that of previous studies suggest species competitiveness within the area. The predominance of Anopheles arabiensis at Iwo road, Bodija and Eruwa also supports the hypothesis. The ratio of sympatry between Anopheles colluzzi and Anopheles gambiae s.s. in our study was 95:5 at Oyo and 50:50 at Eruwa. Previous studies in Oyo State have reported the ratio as 39:61 (Awolola et al., 2005); 35:65 (Awolola et al., 2007) and 100:0 (Djouaka et al., 2007; 2008). The varying frequencies of these species in different studies around the same region for samples that were collected around the same period of the year may be attributed to changes in species dynamics which is hence recommended for further studies.

4 Conclusions

The high DDT resistance recorded in this study may limit the effectiveness of ongoing scale up of LLIN intervention in Oyo state because of cross resistance. Proper monitoring of resistance and surveillance is hence required to inform policy decision.

Authors’ contributions

A.O.A. conducted both the field and laboratory study and wrote the manuscript. K.O.K.P. supervised the entire experiment. A.O.O. assisted in field collections and writing of manuscript. A.K.O. analyzed the data. Awolola T.S. supervised the entire experiment. All authors read and approved the final manuscript.

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