Seasonal Diversity in Mosquito Larval Ecology and Its Public Health Implications in Urban Slums of Lagos, Nigeria

ABSTRACT.

Mosquito-borne diseases (MBDs) are major public health burdens in tropical nations, including Nigeria. This study assessed mosquito larval species composition, abundance, and abiotic factors influencing mosquito breeding in slum communities of Lagos with the goal of informing MBD control measures. Three slum communities—Bariga, Makoko, and Ajegunle—were selected along with the nonslum community of Ikeja, which served as a control site. Larval sampling was done using the standard dipping technique between December 2021 and July 2022 across the dry and wet seasons. Mosquito larvae were raised to adults and identified using morphological keys and molecular assays. A total of 57,753 immature mosquitoes were collected from all study sites, with a significantly (P < 0.05) greater abundance in the dry season than the wet season. The majority (98.1%) of the mosquitoes collected belonged to Culex pipiens s.l., the only species found during the dry season in almost all locations. In the wet season, species identified from all sites combined were Anopheles gambiae ss., Anopheles arabiensis, Aedes aegypti, Aedes albopictus, Cx. pipiens s.l., and Lutzia tigripes, with Ajegunle having the greatest species diversity (H = 0.593). Among physicochemical parameters measured, only water temperature had a significant positive correlation (r = 0.934, P = 0.020) with larval densities in Ajegunle only. Permanent mosquito-breeding habitats had significantly greater larval densities than temporary habitats within the slum communities. These findings could inform the development of integrated vector control strategies that address the different species of mosquitoes in the fight against MBDs in urban slums.

INTRODUCTION

Mosquitoes are insects of public health importance because of their role in transmitting several pathogens to humans that cause diseases such as malaria, yellow fever, lymphatic filariasis, and other mosquito-borne diseases (MBDs) in tropical countries. Malaria causes almost a million deaths annually and Nigeria accounts for a quarter of global cases.¹ In 2017, yellow fever in Nigeria resurged after 15 years, and annual outbreaks of the disease have been reported in different regions in the country, putting 160 million people at risk.² Nigeria ranks third in global prevalence of lymphatic filariasis, one of the neglected tropical diseases with significant morbidity that affects mostly the rural poor.³ These diseases still remain endemic in the country despite control efforts toward malaria,¹ vaccination campaigns against yellow fever,⁴ and mass drug administration for lymphatic filariasis control.³

Given the COVID-19 pandemic and the considerable attention it received, the WHO warned that other highly infectious diseases such as malaria may become neglected, leading to a spike in the number of cases.⁵ It is therefore necessary to intensify efforts to combat MBDs including through surveillance and control of mosquito vectors. Mosquitoes have aquatic juvenile stages, and control of these immature forms (larval control) is an effective way of preventing and controlling MBDs because it nips the problem in the bud by reducing mosquito populations during their immature stages.⁶ To carry out control of mosquito larvae either by larviciding or environmental management, a good knowledge and understanding of the mosquito larval ecology is a prerequisite. In disease-endemic areas, including Nigeria, where malaria still kills a child every minute,¹ studies on mosquito larval ecology have been limited to rural areas, leaving the urban areas understudied.^7,8

The most populous commercial center in Africa is Lagos State, Nigeria, with an estimated population of 24 million, and two thirds of its inhabitants are economically disadvantaged. There are many slum communities in Lagos, which are usually characterized by huge piles of waste, blocked drainage systems, and littered containers that all could serve as breeding habitats for mosquito vectors when rainwater collects in them. In these slums, the residents are known to have a low level of formal education and live in unhygienic conditions and poverty.⁹ Among the MBDs, malaria is the most prevalent in Lagos, accounting for 60% of outpatient hospital cases and 30% mortality in children younger than 5 years of age.¹⁰ To the best of our knowledge, no study has investigated explicitly the extent to which urban slums contribute to mosquito breeding habitats, populations, and MBDs in Lagos. With the changing climate, which is increasing the geographic expansion of vector populations and the risk of pathogen transmission,¹¹ it becomes imperative to understand the ambient environmental conditions that support breeding of mosquito vectors in these endemic slum communities.

Thus, our study focused on slums in Lagos in a bid to inform targeted and integrated vector control measures to complement current interventions such as indoor residual insecticide spraying and long-lasting insecticide-treated bed nets, which mainly target the adult stage of mosquito in Lagos State. The specific objectives of our study were to determine mosquito larval habitat types, distribution, habitat occupancy, species composition, larval densities, and the ambient physicochemical parameters and climatic factors that influence mosquito breeding habitats in slum communities in Lagos. On a broader scale, this study will help in attaining the WHO Global Vector Control Response targets,¹² as well as the United Nations’ Sustainable Development Goal (SDG) 3, “Good Health and Well-being,” by the year 2030.

MATERIALS AND METHODS

Study area.

Three slum communities—Ajegunle, Makoko, and Bariga—were selected for this study, as well as a nonslum community, Ikeja, which served as a control site. These communities are located in the Ajeromi-Ifelodun, Lagos mainland, Somolu, and Ikeja local government areas, respectively, in Lagos State, Nigeria. Lagos lies along the west coast of Africa (lat. 6°22'–6°42'N, long. 2°42'–3°22'E). The slum communities were selected because they are among the most notable slum communities in Lagos and have largely been neglected for mosquito surveillance studies. They are characterized with filth, lack of infrastructure, poor housing, and unsanitary conditions.⁹ We hypothesized there will be seasonal variations in larval ecology between slum communities and the nonslum community.

Mosquito larval sampling and species identification.

Sampling of immature mosquitoes was carried out using systematic random sampling that targeted the perimeter of each study area. All accessible, open, potential aquatic habitats of mosquito larvae were surveyed two times each during the dry and wet seasons in a cross-sectional study design approach. The dry season spanned from December 2021 to March 2022 whereas the wet season occurred from April to July 2022. Mosquito-positive larval habitats (i.e., habitats that had mosquito immature stages [larva and/or pupa]), were identified and classified into ground pools, gutters/open drains, discarded tires, and other containers, similar to a previous study.¹³ These habitat classes were grouped further into permanent and temporary breeding habitats.¹⁴ Permanent habitats included gutters and canals, which occurred in both the dry and wet seasons, whereas temporary habitats included ground pools, discarded tires, and other containers, which mainly occurred during the wet season.

The larvae were collected with the aid of a standard WHO 350-mL dipper (John W. Hock Company, Gainesville, FL), but in few instances where the habitat water was too shallow to use the dipper, larvae were collected using a 60-mL ladle. For each habitat sampled, five dips or scoops of the water were taken and the mosquito larval density was estimated as the number of larvae (and/or pupae) per dip.¹⁵ A GPS device (eTrex^® 10; Garmin Ltd., Olathe, KS) was used to record the coordinates of both potential and positive mosquito breeding habitats found. All larvae collected were stored in well-labeled bottles with the habitat water and were transferred to the entomology laboratory at the Department of Zoology, University of Lagos, Nigeria. Larvae were reared to the adult stage in mosquito cages and identified using standard morphological keys.^16,17 Cryptic species in the Anopheles gambiae complex, the malaria parasite vector, were identified further using polymerase chain reaction at the molecular entomology laboratory of Osun State University, Osogbo, Nigeria.¹⁸

Abiotic factors influencing mosquito habitat occupancy and larval abundance.

During the sampling, breeding sites were analyzed for abiotic factors influencing their mosquito larval presence or absence, distribution, and abundance in both the dry and wet seasons. Potential breeding sites without mosquito larvae (negative sites) were analyzed as controls. Fourteen physicochemical parameters were assessed, of which water temperature, pH, conductivity, dissolved oxygen, total dissolved solids (TDS), and salinity were measured in situ using a water-quality meter (Extech™ dissolved oxygen meter; Extech Instruments, Nashua, NH), which was calibrated before use. Water samples were collected from the larval habitats in three replicates and measured for biological oxygen demand, and nitrate and phosphate levels ex situ at the central research laboratory of the University of Lagos using an ultraviolet–visible spectrophotometer.¹⁹ Heavy metals, including copper, chromium, iron, lead, and zinc, were also analyzed using atomic absorption spectrophotometry.²⁰ Ambient air temperature and relative humidity were measured using a handheld enviro-meter (Traceable^®; Traceable Products, Webster, TX).

Data analysis.

Data collected were subjected to descriptive and inferential statistics to determine significant differences among study sites. Wet and dry season data were compared using the t-test. Analysis of variance was used to compare data among study communities. Pearson’s correlation was used to determine the influence of abiotic factors on larval abundance. Statistical analyses were carried out using SPSS (version 23; SPSS Inc., Chicago, IL). Shannon and Simpson indices were used to determine species diversity using PAST (version 4.11; University of Oslo, Oslo, Norway) software. For all statistical tests, P < 0.05 was considered statistically significant. The GPS coordinates from the sampled mosquito larval habitats were entered into ArcGIS (version 10.5; Esri, Redlands, CA) and were used to generate a map of the study area that shows the spatial distribution of the mosquito larvae identified (Figure 1).

Figure 1.

Map showing the spatial distribution of mosquito larvae breeding during the dry and wet seasons in the study communities in Lagos State, Nigeria: (A) Bariga, (B) Makoko, (C) Ajegunle, and (D) Ikeja. Color codes denote mosquito species identified from larval habitats.

RESULTS

Larval habitat occupancy and densities between seasons.

One hundred thirty-one potential breeding sites/habitats were observed during the survey, with 94 (71.8%) positive for mosquito larvae in the study communities. During the wet season, 62 mosquito-positive breeding sites were encountered, which was almost two times greater than that of the dry season (n = 32) in all communities combined. Permanent mosquito breeding sites (Figure 2) had significantly greater larval densities than temporary mosquito breeding sites (Figure 3) within the slum communities, but not in the nonslum community, during the wet season. Temporary breeding sites were largely absent in the dry season except for a tire found in Bariga and a ground pool in Makoko. Across the study sites, there was significant variation (F = 6.544, df = 3, P = 0.002) in larval densities of permanent sites in the dry season, with Ajegunle having the greatest abundance (864.7 ± 343.3 larvae per dip), whereas Ikeja had the least (63.9 ± 30.1 larvae per dip). In the wet season, there was no significant difference in larval densities among study communities for both permanent sites (F = 1.087, df = 3, P = 0.367) and temporary sites (F = 0.894, df = 3, P = 0.457) (Figure 4).

Figure 2.

Representative pictures showing types of temporary mosquito larval habitats found during the study: (A) ground pool, (B) tires, and (C) and (D) discarded containers.

Figure 3.

Representative pictures showing types of permanent mosquito larval habitats found during the study: (A) gutter and (B) canal.

Figure 4.

Mean larval densities of immature mosquitoes collected from permanent and temporary mosquito breeding sites across the dry and wet seasons in the study communities.

Relative abundance of species identified between seasons.

A total of 57,753 mosquito larvae were collected from all study sites, with a significantly greater abundance during the dry season than the wet season (Table 1). However, more mosquito species were obtained during the wet season than the dry season, with five species identified altogether from the study sites: Anopheles gambiae s.l., Aedes aegypti, Aedes albopictus, Culex pipiens s.l., and Lutzia tigripes. The majority (98.1%) of the mosquitoes collected belonged to C. pipiens s.l., which was the only species recorded during the dry season in all study sites except Ajegunle, where Ae. aegypti was also found. Culex pipiens s.l. was significantly abundant during the dry season compared with the wet season in all slum communities (Bariga: t = 2.184, df = 16, and P = 0.0440; Makoko: t = 3.361, df = 17, P = 0.004; and Ajegunle: t = 2.812, df = 10, P = 0.018), but not in Ikeja, the nonslum community. Lutzia tigripes was recorded in only two sites, Ajegunle and Ikeja, during the wet season. Species diversity of mosquitoes ranged from low to average in all study sites, with Ajegunle having the greatest species diversity (H = 0.593), although the greatest number of species was obtained in Ikeja (Table 1). Molecular assays showed that the sibling species of An. gambiae s.l. from all habitats was An. gambiae s.s., except for Bariga, where Anopheles arabiensis was also recorded (Figure 5). Anopheles arabiensis was found breeding sympatrically with An. gambiae s.s. in a ground pool. The relative abundance of anophelines and culicines by breeding habitat types are documented in Table 2. In general, anopheline mosquitoes were found in all study locations during the wet season and were frequently found coexisting with other mosquito species (Culicinae) in various habitat types, including ground pools in Bariga and Ajegunle, gutters in Makoko, and tires in Ikeja.

Table 1.

Relative abundance of immature mosquito species in the wet and dry seasons across study communities

Species composition	Study community and season																Total
	Bariga				Makoko				Ajegunle				Ikeja
	Dry		Wet		Dry		Wet		Dry		Wet		Dry		Wet
	n	%	n	%	n	%	n	%	n	%	n	%	n	%	n	%	n	%
Anopheles gambiae s.l.	0	0.0	12	0.8	0	0.0	116	8.6	0	0.0	329	12.3	0	0.0	39	2.2	496	0.9
Aedes aegypti	0	0.0	170	10.9	0	0.0	84	6.2	26	0.1	157	5.9	0	0.0	140	8.0	577	1.0
Aedes albopictus	0	0.0	0	0.0	0	0.0	0	0.0	0	0.0	0	0.0	0	0.0	9	0.5	9	0.0
Culex pipiens s.l.	9,773	100.0	1,372	88.3	15,500	100.0	1,154	85.2	21,618	99.9	2,184	81.8	3,517	100.0	1,545	88.8	56,663	98.1
Lutzia tigripes	0	0.0	0	0.0	0	0.0	0	0.0	0	0.0	1	0.0	0	0.0	7	0.4	8	0.0
Total	9,773	16.9	1,554	2.7	15,500	26.8	1,354	2.3	21,644	37.5	2,671	4.6	3,517	6.1	1,740	3.0	57,753	–
Shannon index (H)	0	–	0.390	–	0	–	0.520	–	0.009	–	0.593	–	0	–	0.444	–	–	–
Simpson index (1 – D)	0	–	0.209	–	0	–	0.263	–	0.002	–	0.313	–	0	–	0.205	–	–	–
Evenness (eH/S)	1	–	0.492	–	1	–	0.561	–	0.505	–	0.452	–	1	–	0.312	–	–	–

D = dominance; e = exponential constant; H = Shannon diversity index; S = species richness.

Figure 5.

Representative gel electrophoresis image for molecular identification of Anopheles gambiae s.l. samples from the study sites. Lane 1 = 100-bp DNA ladder, Lanes 2 to 7 and 9 to 16 = An. gambiae s.s. (from Bariga, Makoko, Ajegunle, and Ikeja), Lane 8 = Anopheles arabiensis (from Bariga), The molecular weight of An. gambiae s.s. is 390 bp whereas the molecular weight of An. arabiensis is 315 bp.

Table 2.

Relative abundance of anopheline and culicine mosquitoes by habitat type in the study communities

Habitat category	Habitat type	Mosquito taxa	Bariga, n		Makoko, n		Ajegunle, n		Ikeja, n		Total (N = 57,753)
			DS	WS	DS	WS	DS	WS	DS	WS	n	%
Permanent	Gutter	Anophelinae	0	0	0	74	0	0	0	5	79	0.1
		Culicinae	9,773	1,332	14,275	1,054	21,618	2,147	3,517	1,522	55,238	95.6
	Canal	Anophelinae	0	0	0	0	0	0	0	0	0	0.0
		Culicinae	0	0	0	100	0	0	0	0	100	0.2
Temporary	Ground pool	Anophelinae	0	12	0	41	0	329	0	0	382	0.7
		Culicinae	0	40	1,183	1	0	9	0		1,233	2.1
	Tire	Anophelinae	0	0	0	0	0	0	0	34	34	0.1
		Culicinae	0	170	0	70	26	69	0	179	514	0.9
	Other discarded containers	Anophelinae	0	0	0	0	0	0	0	0	0	0.0
		Culicinae	0	0	42	14	0	117	0	0	173	0.3

DS = dry season; WS = wet season.

In situ physicochemical parameters of breeding habitats.

There were no significant differences in levels of in situ physicochemical parameters between mosquito-positive and mosquito-negative sites throughout in all study communities during the dry season (Table 3). The situation was similar during the wet season, except in Ikeja, which had a significant difference between positive and negative sites for three of the parameters: conductivity, TDS, and salinity (Table 4). Conductivity was significantly (t = –2.470, df = 12, P = 0.029) less in the mosquito-positive sites (0.8 ± 0.1 ms/cm) than in the mosquito-negative sites (1.3 ± 1.2 ms/cm). Total dissolved solids was significantly (t = –2.460, df =12, P = 0.030) less in the mosquito-positive sites (0.6 ± 0.1 g/L) than in the mosquito-negative sites (0.9 ± 0.1 g/L). Salinity in positive sites was 0.4 ± 0.04 ppt, which was significantly less (t = –2.185, df = 12, P = 0.049) than that of the negative sites (0.6 ± 0.1 ppt).

Table 3.

Mean values of in situ physicochemical parameters in various locations for mosquito-positive and -negative breeding habitats during the dry season

Physicochemical parameter	Study community and positive/negative mosquito breeding site (± SEM)
	Bariga		Makoko		Ajegunle		Ikeja
	Positive	Negative	Positive	Negative	Positive	Negative	Positive	Negative
Water temperature, °C	29.1 ± 0.4	28.9 ± 0.3	28.9 ± 1.1	30.8 ± 1.5	28.1 ± 0.4	28.9 ± 0.7	29.4 ± 1.0	30.3 ± 2.1
pH	6.9 ± 0.4	8.2 ± 1.3	7.0 ± 0.4	7.5 ± 0.5	6.5 ± 0.6	7.0 ± 0.2	8.0 ± 0.2	8.1 ± 0.5
Conductivity, ms/cm	2.3 ± 0.8	1.5 ± 1.2	3.6 ± 0.7	2.6 ± 0.6	1.1 ± 0.4	1.6 ± 0.2	1.3 ± 0.2	0.8 ± 0.2
DO, mg/L	0.7 ± 0.1	2.6 ± 2.1	3.5 ± 2.6	2.1 ± 0.4	0.9 ± 0.4	1.1 ± 0.5	0.04 ± 0.0	0.4 ± 0.2
TDS, g/L	1.4 ± 0.5	0.8 ± 0.6	2.6 ± 0.6	2.0 ± 0.3	0.8 ± 0.2	1.1 ± 0.1	0.8 ± 0.1	0.5 ± 0.1
Salinity, ppt	1.2 ± 0.4	0.8 ± 0.7	1.8 ± 0.4	1.4 ± 0.3	0.6 ± 0.1	0.8 ± 0.1	0.7 ± 0.1	0.4 ± 0.1

DO = dissolved oxygen; SEM = standard error of the mean; TDS = total dissolved solids.

Table 4.

Mean values of in situ physicochemical parameters in various locations for mosquito-positive and -negative breeding habitats during the wet season

Physicochemical parameter	Study community and positive/negative mosquito breeding site (± SEM)
	Bariga		Makoko		Ajegunle		Ikeja
	Positive	Negative	Positive	Negative	Positive	Negative	Positive	Negative
Water temperature, °C	32.0 ± 0.8	32.5 ± 1.5	30.2 ± 0.4	30.2 ± 0.0	32.1 ± 0.4	31.5 ± 0.8	31.6 ± 0.8	30.8 ± 1.5
pH	7.4 ± 0.2	7.2 ± 0.4	7.1 ± 0.2	7.0 ± 0.0	7.6 ± 0.2	7.3 ± 0.0	7.1 ± 0.3	7.2 ± 0.1
Conductivity, ms/cm	1.3 ± 0.2	1.9 ± 1.0	1.7 ± 0.3	0.92 ± 0.0	1.1 ± 0.3	1.9 ± 0.8	0.8 ± 0.1*	1.3 ± 1.2
DO, mg/L	0.1 ± 0.03	0.1 ± 0.1	0.3 ± 0.1	0.1 ± 0.0	0.2 ± 0.1	0.2 ± 0.1	0.1 ± 0.02	0.2 ± 0.02
TDS, g/L	0.9 ± 0.2	1.5 ± 0.8	1.2 ± 0.2	0.6 ± 0.5	0.8 ± 0.2	1.4 ± 0.6	0.6 ± 0.1*	0.9 ± 0.1
Salinity, ppt	0.6 ± 0.1	1.0 ± 0.5	0.8 ± 0.2	0.5 ± 0.0	0.5 ± 0.1	1.0 ± 0.5	0.4 ± 0.04*	0.6 ± 0.1

DO = dissolved oxygen; SEM = standard error of the mean; TDS = total dissolved solids.

^*Significant difference (P < 0.05) between the positive and negative sites.

When parameters were compared between seasons within mosquito-positive permanent sites only, there was significant differences (P < 0.05) in some parameters between the dry and wet seasons. At Bariga, water temperature and dissolved oxygen were significantly greater in the wet and dry seasons, respectively. In Makoko, conductivity and salinity were significantly greater in the dry season. In Ajegunle, only water temperature was significantly greater in the wet season, whereas at Ikeja, pH was the only parameter significantly greater during the dry season.

There were no significant correlations between in situ water physicochemical parameters and larval densities, nor between climatic factors and larval densities in all sites in both seasons, except for Ajegunle in the dry season, which had a significant positive correlation (r = 0.934, P = 0.020) between larval density and water temperature.

Ex situ physicochemical parameters of breeding habitats.

Results of ex situ physicochemical parameter analysis showed that at Makoko, significantly greater levels of lead (P = 0.047, t = 2.828, df = 4) were found in mosquito-positive habitats compared with negative habitats (Table 5). There were no significant differences in other parameters between positive and negative habitats. At Ajegunle, our results show that phosphate was the only parameter with a significant difference (P = 0.001, = 9.077, df = 4) between mosquito-positive (1.0 ± 0.03 mg/L) and -negative habitats (0.6 ± 0.02 mg/L). At Ikeja, of the parameters, only nitrate was significantly greater (P = 0.0001, t = 30.751, df = 3) in the mosquito-positive habitats. When the parameters in mosquito-positive habitats were compared among the various study sites, there were significant variations in levels of BOD (P = 0.018, F = 6.199, df = 3), phosphate (P = 0.045, F = 4.263, df = 3), and copper (P = 0.037, F = 4.640, df = 3) only.

Table 5.

Mean values of ex situ physicochemical parameters in various locations for permanent mosquito-positive and -negative breeding habitats during the dry season only

Physicochemical parameter	Study community and positive/negative mosquito breeding site (± SEM)
	Bariga		Makoko		Ajegunle		Ikeja
	Positive	Negative	Positive	Negative	Positive	Negative	Positive	Negative
BOD, mg/L	23.4 ± 0.1	23.4 ± 0.01	24.3 ± 0.1	23.9 ± 0.1	23.81 ± 0.28	23.75 ± 0.31	23.7 ± 0.04	23.7 ± 0.1
Nitrate, mg/L	4.4 ± 0.8	3.9 ± 0.1	8.1 ± 1.9	2.8 ± 1.0	4.1 ± 1.1	6.8 ± 1.03	6.0 ± 0.1*	1.1 ± 0.2
Phosphate, mg/L	0.5 ± 0.3	0.7 ± 0.1	1.0 ± 0.1	0.9 ± 0.1	1.0 ± 0.03*	0.6 ± 0.02	0.4 ± 0.1	0.3 ± 0.1
Copper, ppm	1.1 ± 0.9	0.2 ± 0.0	0.1 ± 0.1	0.6 ± 0.2	1.7 ± 0.8	0.1 ± 0.1	3.3 ± 0.4	3.2 ± 0.2
Chromium, ppm	1.2 ± 0.2	1.6 ± 0.0	1.1 ± 1.1	0.2 ± 0.0	1.9 ± 1.5	3.2 ± 0.8	1.4 ± 0.1	1.6 ± 0.1
Iron, ppm	1.5 ± 1.0	4.6 ± 0.0	10.9 ± 6.2	16.3 ± 15.9	18.9 ± 15.9	0.4 ± 0.1	13.4 ± 5.3	7.0 ± 2.6
Lead, ppm	0.5 ± 0.1	0.3 ± 0.1	0.3 ± 0.1*	0.1 ± 0.1	0.4 ± 0.2	0.3 ± 0.1	0.4 ± 0.1	0.4 ± 0.04
Zinc, ppm	4.2 ± 2.3	1.0 ± 0.6	1.2 ± 0.3	6.8 ± 6.8	33.8 ± 29.2	6.4 ± 6.1	5.5 ± 1.5	3.3 ± 0.9

BOD = biochemical oxygen demand; SEM = standard error of mean.

^*Statistical significance (P < 0.05) between positive and negative sites.

DISCUSSION

Mosquito-borne diseases continue to threaten lives and livelihoods in sub-Saharan Africa, with malaria responsible for the greatest burden, claiming almost 1 million lives annually.¹ Urban slums, characterized by a great amount of filth, unhygienic conditions, poverty, lack of infrastructure, and a sprawling population, are rife in Lagos State, the commercial nerve center of Nigeria.⁹ Our has provided empirical evidence that urban slum communities promote mosquito-breeding grounds with a significant variation in abundance of mosquito larvae based on season, habitat type, and species. During the wet season, there was a significantly greater number of breeding sites, but a lower larval density than the dry season across study communities. This was likely a result of greater rainfall during the wet season that filled up discarded containers, thus increasing the number of temporary mosquito breeding habitats. On the other hand, the lower mosquito larval density and abundance obtained during the wet season could have been a result of the heavy rainfall during the wet season, which would have washed away mosquito larvae. This finding agrees with a previous study²¹ that reported greater larval densities during the dry season than the wet season in Kenya. However, it contrasts with another previous study⁸ that reported a greater abundance of mosquitoes during the wet season compared with the dry season in Lagos, although that study reported there was only a brief dry season and two wet seasons during the sampling year. In our study, permanent breeding grounds sustained mosquito abundance during the dry season when temporary container habitats were sparse. The permanent habitats included gutters and canals, which were mostly clogged with refuse and contained wastewater from domestic runoff as the likely water source during the dry season.

Our study revealed the presence of several mosquito species in urban slum communities. With the exception of L. tigripes, all other species found are known vectors that transmit deadly disease-causing pathogens. Anopheles gambiae s.l., the main malaria vector in Africa,^1,22 was found in all four study communities, of which the sibling species occurring in the sites were An. gambiae s.s., except for Bariga, where An. arabiensis was also found. Over the years, An. gambiae s.s. has been reported to thrive in humid forested regions in rural areas whereas An. arabiensis mosquitoes are common in arid regions in urban areas.²³ The findings of our study contradict this speculation in part as, although Lagos is located in the southwestern, humid part of the country, it is largely an urban state and An. gambiae s.s. occurred in all study locations. This implies there could be a change in the adaptation of these mosquitoes from rural to urban environments. Similar reports^24,25 of An. gambiae s.s. invading urban areas and coexisting sympatrically with An. arabiensis have been documented in other parts of the country, including the states of Oyo and Osun.

It is also interesting to note that anophelines were found breeding sympatrically with culicines in habitats not commonly reported, including gutters and tires. Anopheles gambiae s.l. is normally known to breed in open sunlit pools,²⁶ but our study shows that this species can use a variety of habitats, including artificial containers, which is consistent with recent reports.^27,28 The implication for vector control is that larviciding should be targeted at container habitats as well as (and not only limited to) ground pools. Surveillance and control of mosquito vectors in urban areas is especially important in the light of the current spread of the urban invasive malaria vector Anopheles stephensi, into Africa.²⁹ Culex pipiens s.l. was the predominant species found during the dry season, but in the wet season other species were found. The near absence of other species, including the malaria vector during the dry season in most of the study locations, could be attributed to the paucity of breeding sites during the dry season. It could also be because the sampling in our study did not cover the backyards of houses where water-holding containers could have sustained breeding of other mosquito species. Nonetheless, in agreement with our study, An. gambiae s.l. has been reported to occur more during the wet season, which coincides with the peak malaria season.⁷ The yellow fever mosquito Ae. aegypti was found in all locations, whereas the Asian tiger mosquito Ae. albopictus was found in Ikeja only. Overall, mosquito abundance was lowest in the nonslum control site, Ikeja, relative to the slum communities, which lends credence to our study hypothesis.

The results of our study show that conductivity, TDS, and salinity were the only water physicochemical parameters influencing the presence or absence of mosquito larvae. These parameters were significantly less in habitats where mosquito larvae were present than in habitats without mosquito larvae in Ikeja, the nonslum community, but not in the slum communities. This suggests that in urban slum communities, mosquitoes show no predilection for breeding sites based on water chemistry. Also, based on the results of our study, it appears that the in situ physicochemical parameters and climatic factors (air temperature and relative humidity) we measured do not influence mosquito larval densities and abundance significantly, regardless of season and site. The exception was in one community, Ajegunle, where water temperature had a significant positive correlation with larval density. This result indicates that the higher the water temperature, the greater the larval density and vice versa. Recent studies^30,31 have reported a similarly high correlation between mosquito larval densities with temperature and dissolved oxygen. Among the ex situ physicochemical parameters measured, significantly greater levels of lead and phosphate were seen in mosquito-positive habitats than -negative habitats in slum communities, whereas nitrate was found at high levels in Ikeja, suggesting that heavy metals and salts may affect mosquito breeding habitats.

CONCLUSION

Our study has uncovered the quantum of mosquito species breeding in urban slum communities and the indices of abiotic factors influencing their presence and abundance in Lagos State. As malaria and other MBDs continue to cause high mortality in tropical climes, and given the changes in climatic conditions, disease control will rely on current bioecology data of mosquito vectors in endemic communities. The findings of our study will inform integrated vector control strategies and policy decisions against malaria and other MBDs in slum communities of Lagos and Africa at large. Larval source reduction by clearing or covering drainage systems, sanitizing to remove discarded containers, and larviciding using safe products could be incorporated to support ongoing malaria control efforts, such as use of insecticide-treated bed nets and indoor residual insecticide spraying. All of these will contribute to achieving the WHO Global Vector Control Response goals and the United Nations’ SDGs, and ultimately will safeguard public health.