Research Article | Open Access
Temitope Ayinde Oluwaseyi1,2, Adedapo Olufemi Adeogun1,3 and Solomon U. Oranusi1,2
1Department of Biological Sciences, College of Science and Technology, Covenant University, Ota, Ogun State, Nigeria.
2Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Ogun State, Nigeria.
3Department of Public Health, Nigeria Institute of Medical Research, Lagos, Nigeria.
Article Number: 10565 | © The Author(s). 2025
J Pure Appl Microbiol. 2025;19(4):3208-3215. https://doi.org/10.22207/JPAM.19.4.61
Received: 05 May 2025 | Accepted: 25 September 2025 | Published online: 08 December 2025
Issue online: December 2025
Abstract

Mosquito-borne diseases, such as malaria, yellow fever, dengue, and chikungunya, pose significant public health challenges, particularly in regions like Ogun State, Nigeria, where ecological and socio-demographic factors facilitate vector proliferation. This study aims to assess the knowledge, attitudes, and practices (KAP) related to mosquito-borne diseases among Ogun State residents, providing insights to guide targeted interventions. A cross-sectional survey was conducted with 450 respondents selected through a multistage sampling technique. Data on socio-demographic characteristics, knowledge, attitudes, and practices were collected using a structured questionnaire. Statistical analysis, including descriptive statistics, chi-squared tests, and linear regression, was performed using R software to identify associations between demographic factors and KAP indicators. The study population was predominantly young adults (mean age: 25.49 years), with more male participants (65.3%) and a nearly even urban-rural split. While 66.4% of respondents had heard of mosquito-borne diseases, only 34.7% and 36.7% identified Anopheles and Aedes mosquitoes as vectors. Preventive practices such as sleeping under mosquito nets (80.8%) were standard, but other measures, including eliminating stagnant water (46.4%) and using insecticides (40.3%), were less prevalent. Attitudes toward diagnostic testing were limited, with most respondents relying on symptomatic recognition rather than confirmatory testing. Significant associations were observed between demographics and KAP indicators. The findings highlight critical gaps in knowledge, attitudes, and practices related to mosquito-borne diseases in Ogun State. Targeted health education, improved access to preventive tools, and community engagement are essential to bridging these gaps and reducing the public health burden of mosquito-borne diseases.

Keywords

Arboviruses, Dengue, Diagnostics, Mosquito-Borne Diseases, Urbanization, Vectors

Introduction

Ogun State, located in Southwestern Nigeria, is a vital link between Lagos and other regions, combining urban centres like Abeokuta with extensive rural communities. Its economy is firmly rooted in agriculture, particularly rice and cocoa, while rapid urbanisation has introduced significant environmental challenges. Poor waste management, stagnant water in rice paddies, and inadequate drainage create ideal breeding sites for mosquito vectors such as Aedes, facilitating arboviral diseases including dengue, chikungunya, and yellow fever.1-3 Studies have reported arboviruses in high-risk areas such as cattle markets, reflecting a troubling convergence of urban development, agricultural practices, and ecological conditions.4,5 While these ecological and infrastructural factors have been extensively documented, there remains limited evidence on community-level responses to these risks in Ogun State. Current research focuses on mosquito ecology and disease prevalence without adequately exploring knowledge, attitudes, and practices (KAP) related to arboviral prevention and control. However, successful vector control depends on informed community participation, including preventive behaviors such as eliminating breeding sites or using insecticide-treated nets. Previous KAP studies in other African contexts demonstrate the framework’s utility in identifying gaps that hinder effective public health interventions.6,7 Despite growing recognition of arboviral threats, there is a critical gap in understanding how socio-demographic factors influence awareness, perceptions, and preventive behaviors in Ogun State. Addressing this gap is essential for designing context-specific strategies to improve community engagement and strengthen vector control efforts. This study, therefore, aims to assess KAP concerning mosquito-borne viral diseases, identify key determinants of preventive practices, and provide evidence-based recommendations for improving disease prevention at the community level.

Materials and Methods

Study Area
Ogun State is an important economic and cultural center located in the southwest of the country. To the south, Lagos State borders the state, Oyo and Osun to the north. Ondo State to the east, and the Republic of Benin to the west. It spans about 16,762 square miles. The population is above 5 million and includes urban areas like Abeokuta and Sagamu, as well as rural agrarian villages like Alabata and Obantoko. This combination of rural and city environments offers a good sample to examine the demographic and environmental forces affecting the rate of mosquito-borne arbovirus incidence.

Study design
A cross-sectional study in Ogun State assessed knowledge, habits, and attitudes (KAP) regarding arboviruses spread by mosquitoes. This plan enabled one-time data gathering to capture the usual patterns of awareness and behavior among people.

Study population
The study population consisted of individuals residing in six locations within Ogun State: Abeokuta, Alabata, Asero, Lafenwa, Obantoko, and Osiele. Participants were selected using a multistage sampling to ensure representation across urban and rural areas.

Inclusion criteria
Adults aged 18 and above who had lived in the study area for at least one year and were willing to provide informed consent.

Exclusion criteria
Individuals who did not give their consent and had not lived in the area for at least one year.

Sample size
450 participants were recruited, ensuring statistical power for subgroup analyses across locations and demographic factors.

Data collection
Data were collected through structured questionnaires to assess knowledge, attitudes, and practices regarding mosquito-borne arboviruses. The questionnaire covered topics such as awareness of diseases (e.g., yellow fever, dengue, chikungunya), understanding of mosquito vectors (Aedes and Anopheles species), and preventive practices (e.g., use of insecticides, elimination of stagnant water). The questionnaire was divided into three KAP domains: Knowledge, Attitudes, and Practices, with a structured scoring system. Knowledge questions were scored 1 point for correct answers and 0 for incorrect or “Don’t know” responses, while multiple-response items awarded 1 point for each correct option. Attitudes were assessed on a 3-point Likert scale (Agree = 2, Neutral = 1, Disagree = 0), and preventive practices were scored 1 point for positive behaviours and 0 for negative ones. Composite scores were categorised as good (≥75th percentile), moderate (50th-74th percentile), or poor (<50th percentile). Content validity was ensured through expert review and adaptation from WHO guidelines and validated KAP surveys.8 A pre-test on 10% of the sample helped refine clarity and cultural appropriateness. Reliability was confirmed using Cronbach’s alpha, with coefficients of 0.81 (Knowledge), 0.78 (Attitude), and 0.74 (Practice), indicating good internal consistency. Test-retest reliability on a subset after two weeks showed a correlation of 0.85, demonstrating stability over time. These measures collectively ensured the questionnaire was valid, reliable, and appropriate for assessing community-level knowledge, attitudes, and practices toward arboviral disease prevention in Ogun State.

Ethical considerations
This study was conducted under the approval of the Covenant Health Research Ethics Committee (CHREC) with approval number CU/HREC/OO and OA/432/24; the study adhered to national and international ethical standards. Written consent was sought from all participants, and anonymity was preserved while omitting the names and using unique codes for the participants. Community leaders in each study area were engaged to facilitate participant recruitment and ensure cultural appropriateness.

Data analysis
The data were analysed using R software, leveraging its advanced statistical and graphical capabilities.

Descriptive statistics
Summary statistics (e.g., mean, median, and percentages) were calculated for demographic variables and KAP indicators.

Cross-tabulations and chi-squared tests
Associations between variables, such as location, disease awareness, occupation, and vector knowledge, were assessed using chi-squared tests.

Regression analysis
Linear regression models were employed to identify predictors of knowledge and preventive practices, with demographic factors such as age, education, and occupation as independent variables.

Visualization
Graphs and tables were generated to illustrate key findings, such as the percentage of participants aware of specific diseases or the prevalence of preventive practices in different locations.

RESULTS

Respondents’ demographic and economic status show several variations and backgrounds influencing knowledge of sickness and prevention methods. Respondents are mainly from Osiele (26.7%), Obantoko (24.9%), and Alabata (23.8%), with little representation from Lafenwa (0.9%) and Abeokuta proper (0.2%), according to Table 1. Almost equally, the rural-urban split has some little more urban respondents (50.2%) than rural ones (49.3%). Males make up 65.3% of the gender distribution, whereas women account for 32.2% of the sample. With a mean age of 25.49 years and a standard deviation of 12.46, showing a young and diverse group, the range of respondent ages is wide. Given the youth population’s preeminence, this demographic distribution indicates the need for customized awareness and intervention initiatives in rural and urban areas.

Table (1):
Socio-Demographic Characteristics of Respondents

Characteristics
Frequency
Percent
Location and Town
Abeokuta
1
0.2
Alabata
107
23.8
Asero
105
23.3
Lafenwa
4
0.9
Obantoko
112
24.9
Osiele
120
26.7
Undisclosed Residence
1
0.2
What part of Abeokuta do you reside in?
Rural
222
49.3
Urban
226
?50.2
Undisclosed Age
2
0.4
Gender
Female
145
32.2
Male
294
65.3
Undisclosed Gender
11
2.4
Age
Mean
25.49
Median
24.00
Std. Deviation
12.463
Range
68
Minimum
7
Maximum
75
N
450

With 57.3% attaining secondary education, followed by college/university attendance (23.1%), followed by college/university attendance (23.1%), 5.3% of respondents said no formal education, Table 2 stresses respondents’ educational and professional profiles. In terms of employment, students (51.8%) and traders (31.1%) make up most of the sample; smaller groups are made up of transporters (8.9%), farmers (3.3%), and government employees (3.6%).

Table (2):
Socio-Economic Characteristics of Respondents

Characteristics
Frequency
Percent
Educational Background
Valid
3
0.7
College/University
104
23.1
Secondary education
258
57.3
Primary education
61
13.6
None
24
5.3
Occupation
Valid
2
0.4
Civil servant
16
3.6
Farmer
15
3.3
Retired
4
0.9
Student
233
51.8
Trading
140
31.1
Transporter
40
8.9

The findings on knowledge reveal significant associations between demographics and disease awareness, as well as essential gaps in vector knowledge among respondents. Table 3 highlights that age is positively associated with malaria knowledge (p = 0.01), suggesting that older participants understand malaria-related topics better. Conversely, educational background (p = 0.01), occupation (p < 0.001), and marital status (p = 0.02) negatively correlate with knowledge, indicating potential disparities in awareness among specific educational and occupational groups. For example, those with lower educational levels or engaged in certain occupations might have limited access to accurate health information. Gender and religion, however, did not significantly influence malaria knowledge, as indicated by their higher p-values (p = 0.13 and p = 0.15, respectively).

Table (3):
Relationship between Demographics and Malaria Knowledge

Predictor
Coefficient
t-value
p-value
Age
0.0086
2.59
0.01
Gender (Male)
0.0503
1.53
0.13
Educational Background
-0.0333
-2.51
0.01
Occupation
-0.0635
-4.69
Marital Status
-0.0775
-2.31
0.02
Religion
-0.0468
-1.43
0.15

Regarding disease awareness, Table 4 and Table 5 shows that 66.4% of respondents had heard of arboviral diseases, with substantial variation across locations. Awareness was highest in Asero (89.5%) and Obantoko (81.3%), while Osiele (50.4%) and Alabata (45.8%) reported lower awareness levels. Table 6 highlights a significant knowledge gap concerning mosquito vectors, with only 34.7% and 36.7% of respondents identifying Anopheles and Aedes mosquitoes, respectively. It also shows that 33.6% of respondents were unaware of the diseases, underscoring the prevalence of misinformation or lack of information within the community. These findings emphasize the critical need for targeted educational initiatives to bridge knowledge gaps, particularly in underrepresented locations and demographics with limited awareness.

Table (4):
Different Location and the level of Arboviral Disease Awareness

Awareness about Arboviral Disease Total
Yes No Undisclosed
Abeokuta 1 0 0 1
Alabata 49 58 0 107
Asero 94 11 0 105
Lafenwa 3 1 0 4
Obantoko 91 19 2 112
Osiele 60 59 1 120
Town Undisclosed 1 0 0 1
Total 299 148 3 450

Table (5):
General Level of Disease Awareness and Knowledge of Anopheles/Aedes Mosquito

Response
Anopheles
Aedes
Disease Awareness Frequency
0 (No)
281
277
148
1 (Yes)
156
165
299

The results on attitudes highlight significant associations between demographics and disease awareness, as well as respondents’ behaviour toward diagnosis and testing. Table 6 demonstrates statistically significant relationships between location and disease awareness (p < 0.001), education and knowledge of Anopheles mosquitoes (p = 0.007), and occupation and knowledge of Aedes mosquitoes (p < 0.001). These findings suggest that geographical, educational, and occupational factors influence attitudes toward mosquito-borne diseases and preventive measures. For instance, individuals in urban locations or those with higher education levels may have more proactive attitudes toward understanding and addressing these diseases than their rural or less educated counterparts. This indicates the potential for tailored interventions to align with demographic nuances.

Table (6):
Relationship between some Selected Factors and Attitudes towards Mosquito-borne Diseases

Test
χ²
df
p-value
Cramér’s V
95% CI (Lower, Upper)
Location / Disease Awareness
73.351
5
2.05 × 10⁻¹⁴
0.39
(0.31, 0.46)
Education / Anopheles Knowledge
12.081
3
0.00711
0.16
(0.06, 0.26)
Occupation / Aedes Knowledge
25.981
5
8.99 × 10⁻⁵
0.23
(0.14, 0.32)

Table 7 provides insight into diagnostic attitudes, revealing that most respondents (148) self-identified symptoms of malaria but did not seek confirmatory tests, while only 21 participants reported tests explicitly conducted for diagnosis. Additionally, a small proportion (26) sought testing after experiencing symptoms, reflecting a gap in proactive health-seeking behaviour. These trends highlight a reliance on symptomatic recognition rather than diagnostic confirmation, which may contribute to underdiagnosis or misdiagnosis, particularly in cases where symptoms overlap with other diseases. This underscores the importance of improving attitudes toward diagnostic testing through awareness campaigns emphasizing the value of confirmatory tests in managing mosquito-borne diseases.

Table (7):
Attitude towards Disease Diagnosis by Participants

Method
Frequency
Tests were conducted to confirm the Disease
21
I had Symptoms of Malaria
148
Tests were conducted for the symptoms of Malaria
26
I had Symptoms of Other diseases
7
Others
24

The findings on practices reveal disparities in adopting arbovirus and malaria prevention measures among respondents. Table 8 highlights that sleeping under mosquito nets is the most commonly practiced and effective preventive measure, with 80.8% of respondents reporting its use. However, other practices, such as eliminating stagnant water (46.4%), chemoprophylaxis (27.1%), and wearing long, loose clothing (26.8%), show significantly lower adoption rates. The low uptake of these practices underscores the need for awareness campaigns to promote their importance in reducing mosquito-borne disease transmission. Furthermore, Table 9 shows that vaccines for arboviruses like yellow fever are widely available and utilized by 98.1% of respondents. Still, awareness and availability of vaccines for chikungunya, dengue, and Rift Valley fever remain minimal, with less than 2.5% reporting access to these vaccines.

Table (8):
Protective Measures against Arboviral Diseases

Measure
Yes (Effective)
No (Not Effective)
Total
Valid Percent
Decide not to say
Sleeping under a mosquito net
235 (80.8%)
56 (19.2%)
291
64.7%
159
Eliminating stagnant water
135 (46.4%)
156 (53.6%)
291
64.7%
159
Chemoprophylaxis
79 (27.1%)
212 (72.9%)
291
64.7%
159
Wearing long, loose clothing
78 (26.8%)
213 (73.2%)
291
64.7%
159

Table (9):
Awareness of Vaccine Availability for Arboviruses

Disease
Vaccine Available (Yes)
Vaccine Unavailable (No)
Total
Valid Percent
Decide not to Say
Yellow Fever
265 (98.1%)
5 (1.9%)
270
60%
180
Chikungunya
4 (1.5%)
266 (98.5%)
270
60%
180
Dengue
6 (2.2%)
264 (97.8%)
270
60%
180
Rift Valley Fever
3 (1.1%)
267 (98.9%)
270
60%
180

In the context of malaria prevention (Table 10), less than half of the respondents engage in practices such as wearing protective clothing (53%), clearing drainages (43.3%), or cutting bushes (46.3%). Even lower adoption rates are seen for measures like using long-lasting insecticidal nets (LLINs) (18.5%) and avoiding outdoor activities in the evening (32.2%). Additionally, only 34.9% reported using door or window nets, and just 40.3% use insecticides effectively. These findings indicate a gap between knowledge and practice, possibly driven by barriers like cost, accessibility, or insufficient awareness. Efforts to improve these practices should focus on increasing accessibility to preventive tools and educating communities on the effectiveness of comprehensive vector control strategies.

Table (10):
Malaria Prevention Practices

Measure
Effective (Yes)
Not Effective (No)
Total
Valid Percent
Decide not to say
Wearing protective clothing
158 (53%)
140 (47%)
298
66.2%
152
Using Long-Lasting Insecticidal Nets (LLINs)
55 (18.5%)
243 (81.5%)
298
66.2%
152
Avoiding outdoor stays in the evening
96 (32.2%)
202 (67.8%)
298
66.2%
152
Keeping doors closed
93 (31.2%)
205 (68.8%)
298
66.2%
152
Using insecticides
120 (40.3%)
178 (59.7%)
298
66.2%
152
Door/window nets
104 (34.9%)
194 (65.1%)
298
66.2%
152
Cutting bushes
138 (46.3%)
160 (53.7%)
298
66.2%
152
Clearing drainages
129 (43.3%)
169 (56.7%)
298
66.2%
152
Avoiding large gatherings
45 (15.1%)
253 (84.9%)
298
66.2%
152
Discarding unused water/containers
96 (32.2%)
202 (67.8%)
298
66.2%
152
Other methods
10 (3.4%)
288 (96.6%)
298
66.2%
152
DISCUSSION

This study reveals important findings about knowledge, attitudes, and practices regarding mosquito-borne diseases among Ogun State residents. Results confirm and contrast with earlier research, providing detailed insights into factors affecting arboviral disease prevention and control. The population was mainly young and male, with strong representation from urban areas like Osiele and Obantoko. This urban focus may indicate better information and healthcare access, matching Shehu et al.’s observations of higher urban awareness due to superior infrastructure and health services.

Despite most respondents having secondary education or higher, disease awareness remained relatively low, showing a disconnect between formal schooling and health knowledge.  Similar gaps in Lagos informal settlements, where moderate education did not translate to adequate mosquito vector and transmission knowledge.9 This reveals ongoing weaknesses in health communication approaches. Additionally, only about one-third correctly identified Anopheles and Aedes mosquitoes as disease carriers, reflecting patterns from previous outbreaks where vector recognition stayed poor even in high-risk areas.4,10 Demographic correlations with knowledge were significant for age but negative for education and occupation, questioning the effectiveness of targeted health education. Similar inconsistencies, emphasizing how socioeconomic inequalities influence malaria prevention behaviors.10 In this research, diagnostic testing misconceptions and reliance on symptoms rather than confirmatory testing further highlight these gaps. Diagnostic difficulties among Ogun State healthcare workers, showing systemic testing barriers for arboviral infections.11

Prevention behaviors showed mixed results. While many respondents used mosquito nets (80.8%), other measures like removing standing water (46.4%) and applying insecticides (40.3%) were underused. These differences match other observations, attributing low uptake of specific prevention methods to logistical constraints and socio-behavioral factors which can cause increased resistance and adaptation in the new environment.9,12 The awareness and use of arboviral disease vaccines like dengue and chikungunya were minimal, reflecting global worries about poor vaccine distribution and community communication.4 These results emphasize urgent needs for context-specific health education programs, better diagnostic access, and stronger prevention interventions. As recent studies recommend, including risk communication and community participation in health policies9,11 could substantially improve disease control efforts. Moreover, public-private partnerships targeting structural barriers like cost, vaccine distribution, and waste management are vital for achieving sustainable vector control and reducing arboviral disease burden in Ogun State.

CONCLUSION

Residents of Ogun State have in-depth insights into the socioeconomic attitudes, knowledge, and behavior surrounding mosquito-borne diseases. Even if formal education is relatively high, the research shows important discrepancies in disease awareness, vector knowledge, and preventive measures. Differences in disease knowledge and underutilization of diagnostic testing and preventive methods between urban and rural areas point to systematic and community-level obstacles in the fight against arboviral diseases. Although sleeping under mosquito nets is a widely followed preventive measure, others, including removing stagnant water and using insecticides, are still underused. These holes highlight the critical need for focused initiatives addressing particular circumstances and encouraging sustainable health behaviors. The research highlights the need to include health education, enhance access to preventive equipment, and increase diagnostic capability. Dealing with these difficulties will enable policymakers, healthcare professionals, and local stakeholders to cooperate to lessen the burden of mosquito-borne diseases and improve public health outcomes in Ogun State and comparable surroundings. Effective prevention and control of vector-borne diseases should ideally entail properly using increased health education campaigns, improved diagnostic ability, better access to preventive tools, community engagement, policy coordination, and monitoring.

Declarations

ACKNOWLEDGMENTS
The authors thank the management of Covenant Applied Informatics and Communication Africa Center of Excellence (CApIC-ACE) for research funding and CUCRID, Covenant University, Ota, Nigeria, for providing the publication support.

CONFLICT OF INTEREST
The authors declare that there is no conflict of interest.

AUTHORS’ CONTRIBUTION
TAO, SUO and AOA conceptualized the study. SUO and AOA supervised the study. TAO wrote the original draft. SUO, AOA and TAO wrote, reviewed and edited the manuscript. All authors read and approved the final manuscript for publication.

FUNDING
This study was funded by the Covenant Applied Informatics and Communication Africa Center of Excellence (CApIC-ACE).

DATA AVAILABILITY
All datasets generated or analyzed during this study are included in the manuscript.

ETHICS STATEMENT
This study was approved by the Ethical Committee, Covenant University, Nigeria, vide approval number CU/HREC/OO & OA/432/24.

INFORMED CONSENT
Written informed consent was obtained from the participants before enrolling in the study.

References
  1. Adesoye OA, Adediran AD, Oyeniyi T, et al. Implications of larval breeding sites on diversity of mosquito species in Suleja Metropolis, Northcentral Nigeria. Dutse Journal of Pure and Applied Sciences. 2024;10(1a):20- 28.
    Crossref
  2. Ogunnupebi TA, Oduselu GO, Elebiju OF, Ajani OO, Adebiyi E. In silico studies of benzothiazole derivatives as potential inhibitors of Anopheles funestus and Anopheles gambiae trehalase. Front Bioinform. 2024;4:1428539.
    Crossref
  3. Bamou R, Mayi MPA, Djiappi-Tchamen B, et al. An update on the mosquito fauna and mosquito-borne diseases distribution in Cameroon. Parasit Vectors. 2021;14(1):527.
    Crossref
  4. Shehu IK, Ahmad H, Olayemi IK, Solomon D, Ahmad AH, Salim H. Knowledge, Attitude, and Practice in Relation to Major Mosquito-Borne Diseases in Urban and Semi-urban Communities of Niger State, Nigeria. Afr J Biomed Res. 2022;25(3):339-346.
  5. Oresegun OA. Mosquito-borne arbovirus surveillance at a cattle market in Ogun state, Nigeria. Record. 2005;80(36):305-305. Record. 2009;84(04):29-29.
  6. Endale A, Michlmayr D, Abegaz WE, et al. Community- based seroprevalence of chikungunya and yellow fever in the South Omo Valley of Southern Ethiopia. PLoS Negl Trop Dis. 2020;14(9):e0008549.
    Crossref
  7. Chipwaza B, Sumaye RD, Weisser M, et al. Occurrence of 4 Dengue Virus Serotypes and Chikungunya Virus in Kilombero Valley, Tanzania, During the Dengue Outbreak in 2018. Open Forum Infect Dis. 2020;8(1):ofaa626.
    Crossref
  8. WHO Department of Control of Neglected Tropical Diseases, WHO Regional Office for Africa, TDR. Assessing African country capacities to prevent, detect, and respond to arboviral disease outbreaks [Internet]. 2021. https://tdr.who.int/newsroom/news/item/11-12-2021-assessing-african-country-capacities-to-prevent-detect-and-respond-to-arboviral-disease-outbreaks
  9. Oforka CL, Omotayo AI, Akarawak EE, Adeleke MA. Knowledge, attitudes, and practices on mosquito control in urban informal settlements of Lagos, southwest Nigeria. J Integr Pest Manag. 2023;14(1):22.
    Crossref
  10. Djoufounna J, Bamou R, Mayi MPA, et al. Population knowledge, attitudes, and practices towards malaria prevention in the locality of Makenene, Centre- Cameroon. Malar J. 2022;21(1):234.
    Crossref
  11. Ipadeola AF, Akinnola OO, Kolawole OM, et al. Prevalence, Seasonality, and Risk Factors of Malaria and Some Arboviral Infections and Co-Infections in Nigeria. Univers J Public Health. 2024;12(6):1084-1098.
    Crossref
  12. Tebamifor ME, Cleanclay WD, Mamudu CO, Ogunlana OO. Surveillance of Wolbachia infection in mosquito species in Ota, Ogun State, Nigeria. Heliyon. 2025;7(4).
    Crossref

Article Metrics

Article View: 290

Share This Article

© The Author(s) 2025. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License which permits unrestricted use, sharing, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.