Next Article in Journal
Silver Nanoparticle-Based Antimicrobial Coatings: Sustainable Strategies for Microbial Contamination Control
Previous Article in Journal
Comparison of Antioxidant and Antibacterial Properties of Five Plants with Anti-Diabetes and Anti-Cancer Potential
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Microbiology Research
Volume 16
Issue 6
10.3390/microbiolres16060109
microbiolres-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Zika Virus in Malaria-Endemic Populations: A Climate Change-Driven Syndemic in the Sudan Savannah, Nigeria

by
Rebecca B. Atai
1,2,
Maryam Aminu
1,*,
Elijah E. Ella
1,
Grace S. N. Kia
3,
Emmanuel T. Obishakin
2,
Helen G. Luka
2,
Ganih S. Joel
2 and
Anyebe B. Onoja
4
1
Department of Microbiology, Ahmadu Bello University, Zaria P.M.B. 1045, Nigeria
2
National Veterinary Research Institute, Vom P.M.B. 1553, Nigeria
3
Department of Veterinary Public Health and Preventive Medicine, Ahmadu Bello University, Samaru, Zaria, Ibadan P.M.B. 1045, Nigeria
4
Department of Virology, University of Ibadan, Ibadan P.M.B. 3017, Nigeria
*
Author to whom correspondence should be addressed.
Microbiol. Res. 2025, 16(6), 109; https://doi.org/10.3390/microbiolres16060109
Submission received: 1 April 2025 / Revised: 17 May 2025 / Accepted: 24 May 2025 / Published: 27 May 2025
Browse Figures
Versions Notes

Abstract

:
Zika and malaria are important vector-borne febrile illnesses in humans. In this study, we determined the circulation of Zika virus and malaria infections, their hotspots, and their predominant clinical features. A cross-sectional study was carried out in six Local Government Areas (LGAs) in Kaduna State, Nigeria, from September 2018 to May 2019. Four hundred and twenty sera were screened for Zika virus (ZV) IgM and IgG, and Plasmodium falciparum antigen using ELISA and immunochromatographic test, respectively. Overall, a seroprevalence of 14.5% was found for Zika, and 9.3% for malaria. Nineteen (4.5%) and thirty-five (8.3%) patients were seropositive for ZV IgM and IgG, respectively. Co-infection rates for Zika (ZV IgM) and malaria (0.5%: 2/420), and for ZV IgG and malaria (0.7%: 3/420) were observed. Lere (10%: 7/70 for ZV IgM), Kachia (14.3%: 10/70 for ZV IgG) and Zaria (18.6%: 13/70 for malaria) LGAs were identified as hotspots for Zika and malaria. Age was significantly associated with malaria (p = 0.008) and ZV IgG (p = 0.004). Patients aged 1–10 years had the highest malaria seroprevalence (18.4%), while those aged 21–30 years had the highest ZV IgM prevalence (6.1%: 7/114). Out of the pregnant patients (56/420) tested, 5.37% (3/56) had antibodies to both recent and past ZV infection. A significant association was found between maculopapular rash (p = 0.021) and Zika, as well as between duration of the fever and recent Zika infection (p = 0.041). We highlight that malaria is endemic in Kaduna and that ZV is silently circulating, providing baseline data for further molecular epidemiological studies.

1. Introduction

Zika Virus (ZV) causes sporadic disease in Africa and Asia [1]. An island in the South Pacific Ocean, the French Polynesia in 2013–2014 documented a zika epidemic involving 32,000 people [2]. In May 2015, Brazil confirmed autochthonous transmission of ZV in the northeast, which has now expanded to multiple countries bordering the Pacific Ocean [3]. ZV belongs to Flaviviridae family of and Flavivirus genus, it is an enveloped positive-stranded RNA virus with a genome size of approximately 11 kb [4]. It consists of a complete open reading frame (ORF) that encodes three structural (capsid (C), envelope glycoprotein (E) and membrane (M) and seven non-structural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) proteins. There are three lineages: the West African (Nigerian cluster), East African (MR766 prototype cluster), and Asian [3,5]
Zika Virus Fever (ZVF) is asymptomatic or symptomatic with an incubation period of 3–14 days [6]. Asymptomatic cases are about 80% and are a major source of transmission [7]. The symptoms are usually mild and last for 2–7 days [8] and include fever, myalgia, headache, non-purulent conjunctivitis, maculopapular rash, and arthralgia in the small joints of hands and feet which could be accompanied by joint swelling [9,10]. Also, anorexia, nausea and vomiting, diarrhoea, abdominal pain, sore throat, retro-orbital pain, a burning sensation of the palms and soles, and vertigo are other symptoms. Complications of Zika include Guillain-Barré syndrome (GBS) and acute disseminated encephalomyelitis (ADEM) in adults and majorly microcephaly in newborns [11,12]. There are two different cycles; the sylvatic cycle occurs in non-human primates, while the urban cycle is between human-mosquito-human [13,14]. This route of transmission is via Aedes aegypti and Aedes albopictus [15]. Factors associated with the spread of ZV include the non-immune population, high population density, tropical climate, inadequate control of Aedes mosquitoes and sociodemographic factors [16,17].
In 2021, the incidence of zika among women globally ranged from 2.41 to 3.39 per 100,000 population [18]. A case was reported in Italy from a traveler returning from the Dominican Republic [19]. In Nigeria, the virus was isolated twice in samples collected from febrile patients between 1971 and 1975 [20], and in a study carried out in 1979, 52% had neutralizing antibodies [21] in Oyo State. Malaria is a major global public health challenge, with an estimated 263 million cases and 597,000 deaths reported in 2023 [22]. Despite efforts to reduce the parasite, it is a major problem in low- and middle-income countries [23]. Co-infection with the Zika virus and malaria is an increasing issue, especially in tropical and subtropical locations such as Nigeria, where both diseases are co-endemic [24]. This complicates diagnosis, treatment, and disease management, as Zika and malaria share overlapping symptoms, such as fever, headache, and fatigue [25]. In resource-limited settings like Northern Nigeria, including Kaduna State, febrile illnesses are often presumptively treated as malaria, potentially leading to missed Zika diagnoses. Hidden Zika virus infections among patients initially suspected to have malaria in parts of northeastern Nigeria (Adamawa, Bauchi, Borno) have been reported [26]. Zika is already a concern among pregnant women due to its congenital implications. And co-infection with Plasmodium falciparum during pregnancy could increase the risk of adverse outcomes such as anaemia, low birth weight, and stillbirths [27]. However, due to clinical similarities and a lack of standard Zika testing, co-infections frequently go unnoticed.
Climate changes cause environmental shifts that promote the re-emergence and transmission of vector-borne diseases [28]. The spread of the Zika virus and malaria is strongly influenced by climatic variables, particularly temperature, rainfall, humidity, and seasonality [29]. And the disease vectors, the mosquitoes—Aedes aegypti for Zika and Anopheles species for malaria—are highly sensitive to changes in environmental conditions. Warmer temperatures accelerate mosquito development, reduce the extrinsic incubation period of pathogens within vectors, and increase biting rates [30]. For Zika, optimal transmission occurs at temperatures between 26 and 29 °C, which enhances viral replication and vector competence in Aedes mosquitoes [31]. Similarly, malaria transmission is favoured by temperatures between 20 and 30 °C, with Plasmodium falciparum development peaking around 25–27 °C [32]. Rainfall is another important factor: it generates breeding places such as stagnant pools, which are necessary for mosquito reproduction. However, severe rainfall or flooding can wash away larvae, and extended droughts can diminish vector populations. In semi-arid zones like Kaduna State, Northwest Nigeria, the interaction of seasonal rainfall patterns and rising temperatures can intensify disease risk by expanding appropriate habitats and extending transmission seasons [33].
In Africa, there is scant data on zika, with a paucity of data on zika and malaria co-infections. Further, abundance of Aedes spp. with an increased report of dengue [34,35,36] suggest the likelihood of silent circulation of ZV in parts of Nigeria. This study determined the sero-prevalence, and clinical features of zika, and identified ZV and malaria co-infection in Kaduna State, Nigeria.

2. Materials and Methods

2.1. Study Area

Kaduna State is located in the Northwestern region of Nigeria with 23 local Government areas (LGAs). There are general and rural hospitals in these LGAs alongside private health facilities. The general hospitals are mostly patronized by people from far and near, and sometimes from outside the LGA, because of subsidized services. There are about 6,113,503 people in the state according to 2006 census however, the population was estimated to reach 9,032,200 in 2022 making it one of the most populous states in Nigeria [37]. The state shares land border with the Federal Capital Territory and Zamfara, Katsina, Niger, Kano, Bauchi, Plateau and Nasarawa states, and is located between latitudes 9°03′ and 11°32′ North of the equator and longitudes 6°05′ and 8°38′ East of the Greenwich meridian. It has 5% of the total land mass of Nigeria, with a size of 46,053 sq km. It is located in the Sudan Savannah Zone on a gentle, undulating plain with land ranging from 500 m to 650 m above sea level [38].

2.2. Study Design

This is a hospital-based cross-sectional survey in which febrile patients were randomly sampled from two LGAs in each senatorial district (SD), namely: Zaria and Lere LGAs (Northern SD), Sanga and Kachia LGAs (Southern SD) and Chikun and Kaduna South LGAs (Central SD). The general hospitals in the LGAs were used for the study because they represented a good cocktail of service users. The study was conducted in Hajiya Gambo Sawaba general hospital, Zaria; Dabo Mohammed Lere memorial hospital, Saminaka; Gwanma Awan general hospital, Kakuri; General hospital, Sabon-Tasha; General hospital, Kachia; and Gwantu general hospital, using the non-probability sampling method, making a total of six hospitals in total. Ethical approval was obtained from the Health Research Ethics Committee of the Kaduna State Ministry of Health (MOH/ADM/744/VOL.1/466—20 February 2018). Informed consent was obtained from all subjects and parents (of children) in the study before commencement of data and sample collection. The age criterion for inclusion was 1 year and above due to difficulty in collecting samples from babies, as their mothers were unwilling to consent.

2.3. Sample Collection

The demographic data of 420 patients and clinical features of Zika and malaria were collected using a structured questionnaire from September 2018 to May 2019. Sample IDs were used to tag the questionnaires and corresponding blood samples from patients. Five millilitres of whole blood were collected by a certified laboratory technician and dispensed into labelled plain sample collection tubes and allowed to clot at room temperature. The tubes with samples were spun at 2500 rpm for 5 min to separate the sera from clotted blood. The resulting sera were aliquoted into two cryovials carrying the sample label for each patient. Samples were stored at −20 °C at the National Veterinary Research Institute, Vom, until required for analyses.

2.4. Serological Assay

Sera were screened by RDT for ZV IgM and IgG antibodies (Zika IgG/IgM Rapid Test Cassette-WB/S/P-10T/Kit, Catalog No.: IZIB-402, CiTEST Diagnostics INC., Vancouver, BC, Canada) and P. falciparum antigen using immunochromatographic kits (Standard Diagnostics Inc., Yongin-si, Republic of Korea) adhering strictly to manufacturer’s instructions. Samples that were positive for both Zika virus antibodies were further screened using Enzyme-Linked Immunosorbent Assay (ELISA) for ZV antibodies using ab213327 anti-Zika virus IgM µ-capture ELISA kit (Lot: GR3328269-2, Abcam Plc, Cambridge, UK). In brief, samples were equilibrated at room temperature for 30 min. One microlitre of the samples were diluted and mixed with 100 μL of sample diluent to achieve a 1:100 dilution. Standards, controls and diluted samples were added to assigned wells, leaving well A1 as the substrate blank. Plates were covered and incubated at 37 °C for 1 h. Contents were discarded, and wells were washed 3 times with 300 μL washing solution. A 100 μL of conjugate was added to all wells except the blank. Another incubation was carried out for 30 min at room temperature, avoiding light. Plates were washed, and 100 μL of tetramethylbenzidine was added and incubated in a dark room for 15 min. A 100 μL of stop solution (0.2 mol/L sulfuric acid) was added to the wells. Absorbance was read immediately at 450/620 nm (DNM-9602 Microplate reader, Wincom, Cincinnati, OH, USA). Results were calculated, and values > 11 were considered as positive, 9–11 as equivocal and <9 as negative.

2.5. Data Analysis

Data obtained from the questionnaire and the results of the laboratory analysis were analysed using R software version 4.1.2/1 to check for association by Chi square statistical tool between the variables and seroprevalence obtained at a 95% confidence interval, and a p-value ≤ 0.05 was considered significant.

3. Results

Out of the 420 patients sampled, 19 patients were positive for ZV IgM, 35 for ZV IgG, 7 for both ZV IgM and IgG, and 39 for malaria. An overall seroprevalence of ZV infection was found to be 14.5% (61/420) and 9.3% for malaria. Seroprevalence of the different ZV antibodies is 4.5% (19/420) for ZV IgM and 8.3% (35/420) for ZV IgG (Figure 1).
Zika virus IgM antibodies equivocal rate of 0.5% (2/420), was recorded among patients. Total ZV IgM and malaria (0.5%: 2/420), and ZV IgG and malaria (0.7%: 3/420) co-infection rates were documented in this study. Seven patients (1.7%: 7/420) were positive for both ZV IgM and ZV IgG while only 1 patient, 93 males, had both ZV antibodies and malaria parasite (Figure 2).
The study population consisted of 40% (167/420) males and 60% (253/420) females. The proportion of females enrolled in this study is higher than that of male patients. ZV antibodies were detected at a higher rate among males (6.0%: 10/167 for ZV IgM and 9.0%: 15/167 for ZV IgG) compared to the female patients (3.6%: 9/253 for ZV IgM and 8.0%: 20/253 for ZV IgG). The male (9.6%: 16/167) and female (9.1%: 23/253) patients had nearly equal malaria seroprevalence rates. There was no statistically significant association (p ˃ 0.05), however, male patients are more likely to have these infections (OR = 1.727; 95% CI = 0.686–4.344; OR = 1.150; 95% CI = 0.571–2.315; 1.060; 95% CI = 0.542–2.071). This result is shown in Table 1.
The youngest of the patients was 1 year old, while the oldest was 93 years old. The total mean age of the patients was 32 years. The difference observed in the seroprevalence of ZV IgG (p = 0.004, df = 5, χ2 = 17.418) and Malaria (p = 0.008, df = 5, χ2 = 15.656) with age was statistically significant. Patients 21–30 years old had the highest ZV IgM prevalence (6.1%: 7/114). A 20.0% (14/70) ZV IgG seroprevalence was documented among patients above 50 years of age, while the lowest (2.0%: 1/49) was among patients 1–10 years old. Conversely, the highest malaria seroprevalence (18.4%: 9/49) was among patients aged 1–10 years old, while none of the patients above 50 years was positive for malaria parasite (Table 2).
The predominant occupation of the patients were students (24.8%: 104/420) while hunters had the least (0.2%: 1/420). Seroprevalence of ZV IgM (6.7%: 3/45) and ZV IgG (17.7%: 8/45) were both highest among the civil servants, while neither ZV antibodies nor malaria antigen was found among hunters. Conversely, the lowest malaria parasite rate (2.2%, 1/45) was among civil servants and the highest (27.3%, 3/11) among artisans, with a significant difference (χ2 = 15.173, df = 6, p = 0.019).
Understanding the demography of the patients by educational status, 27.8% (117/420) of patients had primary education as their highest qualification, 25.9% (109/420) attained the secondary school level, 28.8% (121/420) had tertiary education and 17.4% (73/420) had non-formal education. There was no statistically significant association between educational status and Zika and malaria. About 64.5% (271/420) of the patients were married, 34.8% (146/420) single, and 0.7% (3/420) divorced. Zika and malaria were not prevalent among the divorced patients. Almost equal ZV IgM seroprevalence rates were found among married patients (4.8%: 13/271) and single (4.1%: 6/146). There was a statistically significant association between ZV IgG (p = 0.023, df = 2, χ2 = 7.535), malaria (p = 0.011, df = 2, χ2 = 9.023) and marital status. The highest rate of ZV IgG (11.1%: 30/271) and malaria (15.1%: 22/146) was among married and single patients, respectively. About 22.1% (56/253) of female patients were pregnant, and 5.37% (3/56) had both IgM and IgG antibodies.
The prevalence of Zika and malaria was determined in the LGAs (shown in Table 3 and Figure 3A–C). ZV IgM higher rate (10.0%: 7/70) was observed among patients residing in Lere LGA, while patients enrolled from Sanga LGA had the lowest rate (1.4%: 1/70). The lowest rate of ZV IgG (2.9%: 2/70) was in Zaria LGA, compared to the highest (14.3%: 10/70) among patients in Kachia LGA. Chikun, Sanga, and Lere LGAs had an equal distribution (8.6%: 6/70) of ZV IgG. The highest (18.6%: 13/70) malaria seropositivity was in Zaria LGA, while the lowest (4.3%: 3/70) was in Kaduna South LGA. There was no statistically significant association (ZV IgM p = 0.220; ZV IgG p = 0.292; malaria p = 0.064) between the ZV infection, malaria and location in this study.
Patients with headache had the highest prevalence of ZV IgM (4.8%: 16/332), ZV IgG (8.7%: 29/332), and malaria (A 10.5%: 35/332) while the lowest (3.4%: 3/88 for ZV IgM; 6.8%: 6/88 for ZV IgG; 4.5%: 4/88 for malaria) was among those without headache. Though headache was not statistically associated with Zika and malaria, patients who had malaria were 2 times (p = 0.129, df = 1, χ2 = 2.970, OR = 2.475, 95% CI = 0.855–7.161) more likely to have headache in this study. Eleven (11) patients reported to have maculopapular rash in this study. The highest of ZV IgM (9.1%: 1/11), and ZV IgG (27.3% (3/11) seroprevalence rates were among patients who had maculopapular rash compared to patients who did not (4.4%: 18/409 for ZV IgM, 7.8%: 32/409 for ZV IgG). An equal seroprevalence of malaria was found among patients with (9.1%: 1/11) and without (9.3%: 38/409) rash. A significant association (p = 0.021, df = 1, χ2 = 5.304, OR = 4.418; 95% CI = 1.117–17.475) was identified between rash and ZV IgG in this study. Patients who had myalgia had more ZV IgM antibodies (5.0%: 15/298). An equal distribution of ZV IgG prevalence was observed among patients with myalgia (8.4%: 25/298) and those without myalgia (8.2%: 10/122). Patients with a history of myalgia had 11.1% (33/298) malaria seroprevalence, which is higher than the prevalence (4.9%: 6/122) among patients without myalgia. There was no observed statistically significant association between myalgia and Zika (p = 0.580, df = 1, X2 = 0.617, OR = 1.564; 95% CI = 0.508–4.810 for ELISA ZV IgM, p = 0.361, df = 1, χ2 = 1.330, OR= 1.896; 95% CI= 0.628–5.723 for ZV IgM and p = 1.000, df = 1, χ2 = 0.004, OR = 1.026; 95% CI = 0.477–2.205) but a significant association was observed with malaria (p = 0.048, df = 1, χ2 = 3.894, OR = 2.408; 95% CI = 0.982–5.903).
In this study, data were collected on oedema of the extremities. It was observed that 4.7% (19/402) of patients with no oedema were positive for Zika IgM, while none was positive among those with oedema. Eighty percent (337/420) of the patients had no history of conjunctivitis, while 20% (83/420) had conjunctivitis. Higher prevalence rates of ZV IgM (4.7%: 16/337), ZV IgG (8.9%: 30/337) and malaria (9.5%:32/337) were recorded among patients with no conjunctivitis while the lowest rates, ZV IgM (3.6%: 3/83), ZV IgG (6.0%: 5/83) and malaria (8.4%: 7/83) were among patients with conjunctivitis. There was no statistically significant association between eye discharge, ZV antibodies and malaria (p > 0.05), as equal prevalence of ZV IgM was found among patients with 4.8% (2/42) and without 4.5% (17/378) history of eye discharge. Also, patients with no eye discharge had the highest seroprevalence of ZV IgG (8.5%: 32/378) and malaria (10.1%: 38/378).
The highest prevalence of total ZV antibodies was among patients with arthralgia. A 5.3% (13/243) prevalence of ZV IgM and 9.9% (24/243) of ZV IgG was observed among patients with arthralgia. Conversely, the highest prevalence of malaria (11.3%: 20/177) is among patients with no arthralgia. There was no statistically significant association (p > 0.05) between arthralgia and Zika and malaria. Fever duration was significantly associated with ZV IgM positivity (p = 0.041, df = 2, χ2= 6.296 for ZV IgM). The highest rate of ZV IgM (6.5%: 15/232), and ZV IgG (10.3%: 24/232) were among patients with fever between 2 and 7 days.
Patients’ history of travelling abroad and children with microcephaly were investigated to determine the likelihood of previous exposure and vertical transmission. Only 3.3% (14/420) of the patients travelled abroad, and half of them (50%: 7/14) did not disclose the countries visited. All patients with ZV IgM (4.7%: 19/406), ZV-IgG (8.4%: 34/406), and malaria (9.1%: 37/406) positivity had no history of travelling abroad. Previous history of travelling abroad was not associated with zika and malaria sero-markers. Zika virus antibodies and malaria parasites were not detected among the patients who had children with microcephaly.

4. Discussion

The overall Zika virus infection prevalence rate of 14.5% in this study indicates significant exposure to ZV. Anti-ZV IgM prevalence of 4.5% implies a current infection which has been ongoing silently in the population. This rate could be due to the asymptomatic and self-limiting nature of zika in 80% of cases, which may not have been severe enough for patients to present themselves to the hospital [39]; hence, some cases may have gone unrecognized and unrecorded. Also, self-medication occurs instead of visiting the health facilities when people have febrile symptoms, therefore, this low rate of recent infection observed in this study may have been impacted by this. The rate of recent zika infection is slightly lower than the 6% reported in North Central Nigeria [40] and in a cross-sectional study in Zambia [41]. Zika virus IgG positivity in this study is an indication of some level of immunity in the population; hence, re-emergence in a greater coverage/magnitude and pathogenicity should not be ruled out. Further, the ZV-IgG rate in our present study is higher than 4% reported in North Central Nigeria [40] but lower than 12% recorded by [42] and 14.4% in Plateau State [43]. The overall prevalence of ZV infection obtained in this study may have been impacted by the season (dry) in which the samples were collected, when the population of Aedes spp. was low as previously observed [44,45].
The malaria prevalence (9.3%) in this study reinforces the endemicity of vector-borne malaria in Nigeria. This low prevalence rate agrees with the global reduction in the prevalence of malaria observed from 2015–2021 [22] with measures such as possession and adherence to the use of insecticides treated bed nets (ITNs), reduction of environmental risks and vectors control measures put in place by the government through programmes such as National Malaria Elimination Strategic Plan has contributed to the reduced malaria burden [46]. Among patients who were positive for ZV, only 10.5% of those with current infection had Plasmodium falciparum antigen in their blood. This could mean the febrile condition observed in patients is related to zika in patients with ZV-IgM positivity or to other factors or illnesses in the patients that may distort the normal physiology of the patients, leading to the rise in body temperature. Coinfection is likely due to exposure of patients to malaria and Aedes spp. Within the same period. The low ZV and malaria coinfection in this study could also be due to low ZV prevalence at the time of sample collection. This finding is in contrast to the probable high coinfection in South-eastern Nigeria [42].
The highest ZV IgM prevalence identified in Lere LGA in the Northern senatorial district could be due to the presence of water bodies that serve as breeding grounds for Aedes spp. During the dry season, these water bodies are used for irrigation farming, giving a good vegetation cover that serves as a breeding ground for Aedes spp. Thereby increasing ZV transmission. On the contrary, malaria was more prevalent in Zaria LGA, which is in the Kaduna State Northern senatorial district. This is not in concordance with the findings by [47] that reported the highest malaria parasitaemia in Jaba LGA of Kaduna State, Southern senatorial district. The difference could be due to sampling time/season, which affects vector population or as a result of a lesser sample size by this study relative to that of [47]. The higher prevalence of ZV antibodies in Lere and Kachia LGAS has identified and implicated these areas as ZV hotspots. Both ZV antibodies assayed in this study were detected in all LGAs visited. The cosmopolitan nature of Kaduna State, where people from all over the nation and or globe visit, stay, or transit, makes this finding significant and potentially alarming. Hence, this is an indication that Kaduna State is an epicentre for zika epidemics in Nigeria. Therefore, a one health approach is required to plan and guide intervention activities and prevent massive epidemics.
The majority of the ZV and malaria prevalence found among males could probably be due to their involvement more in the outdoor occupations such as farming activities, which predispose them to mosquito bites. Our finding is in agreement with the high prevalence in males in North-central Nigeria [40]. In contrast, a higher prevalence of ZV among females was reported in Puerto Rico and Bahia, Brazil [48,49]. Pregnant females with ZV-IgM positivity are at high risk of congenital ZV transmission and foetal complications. On the other hand, foetuses of pregnant females with ZV-IgG are at an advantage as they have passive immunity passed on to them that will protect them against ZV. Past exposure and recent infection were observed across all age groups, including those older than 51 years of age. This is in agreement with studies that found neutralizing antibodies in the Nigerian population as far back as the 1950s [50]. This portends impending danger if necessary measures and preparedness against outbreaks are not in place. The herd immunity among this age group signifies protection, thereby reducing the rate of human-to-human zika transmission. Despite the presence of neutralizing IgG antibodies, our study confirms the current circulation of ZV. Zika was higher within the age group 21–30 years. The high frequency of recent infection in this age group could be due to more involvement in recreational and exploration activities, which predispose them to infection. In contrast, the high prevalence of malaria in this study among children between 1 and 10 years old could be attributed to the abundance of anopheline mosquitoes, waned conferred maternal immunity and a lack of substantive immunity to the different strains of plasmodium species. Previous studies also reported a higher incidence of malaria among children within this age group in Nigeria and Zambia, respectively [47,51]. Lack of malaria among patients above 50 years of age in this present study could be due to immunity acquired from repeated exposure to the malaria parasites, leading to undetectable parasitaemia or due to good adherence to protective and preventive measures among this age group.
The distribution of participants enrolled in this study includes students (104/420), Business (99/420) and others (96/420), comprising applicants, housewives, retirees, public servants, corps members, nomads and those in the private sectors. The highest prevalence of ZV-IgM among civil servants could be due to chance, as there was no significant association. Artisans had the highest rate of current zika infection, past zika virus exposure and malaria which could be due to high outdoor exposure based on their jobs, or due to some socio-behavioural characteristics which facilitate contact with vectors. Some of the participants live in rural areas where vectors are more predominant than the urban and suburban especially for malaria [52].
Although education has been associated with better knowledge and infection control practices regarding infectious diseases [53], most people with current and past exposure to zika had tertiary education. This finding is not in agreement with previous reports in Salvador in Brazil and the Philippines, where a positive relationship was found between level of education and the prevalence of ZV infection [54,55].
Increased zika and malaria prevalence were found among patients with headaches. This finding aligns with symptoms of zika, where fever and headache [52] were also reported in a European 34-year-old male volunteer infected with a strain isolated from Nigeria in 1954 [56]. Patients with rash had more ZV antibodies compared to those without rash. This agrees with reports of the presence of maculopapular rash in 90% of confirmed ZV patients from the Yap Islands [57]. Of the 11 patients with rash, only one patient had malaria, implying that maculopapular rash is not a clinical characteristic of malaria. Myalgia was found to be common among patients with current zika infection and malaria in this study. Muscular pain is commonly seen in zika and malaria. This study agrees with the observation of myalgia as a symptom or manifestation of ZV infection [58]. Of the patients with ZV-IgM, 15.8% had conjunctivitis, which was non-purulent and similarly identified in Mexico among zika patients [52]. The highest proportion of patients having current zika with arthralgia in this study can be attributed to ZV, as a low prevalence of malaria was found among patients with arthralgia. Arthralgia has been stipulated as one of the transient symptoms of zika infection [59] and is caused by the immune system’s response to the virus through the release of inflammatory cytokines against the virus. This is in tandem with our findings and with report where arthralgia is the most frequent manifestation of zika that resolves after two weeks in most cases [59]. On the contrary, arthralgia is not among the most common symptoms in malaria [60]. None of the patients who had children with microcephaly had serological evidence of zika and malaria. Most of the patients with current zika infection had fever of two to seven days duration, at which point the viremia begins to wane. This finding agrees with prior studies where high ZV IgM antibody detection was observed during the first week of infection [61,62]. Further, it is consistent with findings of higher ZV-IgM in patients seven days from the onset of fever in the Guinea Savannah region of Nigeria [40]. A limitation in this study is that samples were collected during the dry season from September to May, when the vector population was low, and this may have impacted or reduced the prevalence and rate of coinfection. This short period was insufficient to determine the seasonal distribution of Zika and malaria.

5. Conclusions

This study highlights the endemicity of zika in Kaduna State, Nigeria, with antibodies detected in all the LGAs sampled. Lere and Kachia LGAs were established hotspots for zika as well as Zaria LGA for malaria. Similar clinical characteristics with malaria reduce the suspicion index, hence the condition may go unnoticed and unrecorded. Rash and myalgia were the predominant features of Zika and malaria respectively. Findings from this present study can inform a comprehensive epidemiological survey to determine the true burden of ZV and dual infections in the region. We recommend public awareness creation and education on the modes of transmission, complications, as well as the inclusion of zika screening for febrile episodes as a prevention and control measure.

Author Contributions

Conceptualisation, R.B.A., M.A., E.E.E., G.S.N.K., and A.B.O.; data curation, R.B.A., H.G.L., G.S.J., and E.T.O.; formal analysis, R.B.A., M.A., E.E.E., G.S.N.K., and A.B.O.; funding acquisition, M.A., A.B.O., and R.B.A.; investigation, R.B.A., H.G.L., G.S.J., and E.T.O.; methodology, R.B.A., M.A., E.E.E., G.S.N.K., A.B.O., and E.T.O.; project administration, M.A., E.E.E., G.S.N.K., A.B.O., and R.B.A.; resources, R.B.A., M.A., E.E.E., A.B.O., and E.T.O.; software, R.B.A., M.A., E.E.E., G.S.N.K., and A.B.O.; supervision, M.A., E.E.E., G.S.N.K., A.B.O., and E.T.O.; validation, M.A., E.E.E., G.S.N.K., A.B.O., and E.T.O.; visualisation, M.A., E.E.E., G.S.N.K., A.B.O., and R.B.A.; writing—original draft, R.B.A., M.A., E.E.E., G.S.N.K., A.B.O., E.T.O., H.G.L., and G.S.J.; writing—review and editing, R.B.A., M.A., E.E.E., G.S.N.K., A.B.O., E.T.O., H.G.L., and G.S.J. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the United Nations Trust Fund for Human Security (UNTFHS) grant UNTFHS-CDE-25-02079.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Health Research Ethics Committee of the Kaduna State Ministry of Health and Human Services, Kaduna State, Nigeria (MOH/ADM/744/VOL.1/466—20 February 2018).

Informed Consent Statement

Informed consent was obtained from all subjects in the study.

Data Availability Statement

All data presented in this study are available upon request from the corresponding author.

Acknowledgments

The authors acknowledge the support of the National Veterinary Research Institute, Vom, Nigeria for the purchase of some of the reagents used for the work.

Conflicts of Interest

All authors have no conflicts of interest to declare.

Abbreviations

The following abbreviations were used in the manuscript:
LGALocal Government Area
ZVZika Virus
IgGImmunoglobulin G
IgMImmunoglobulin M
ELISAEnzyme Linked Immunosorbent Assay
RNARibonucleic Acid
ORFOpen Reading Frame
CCapsid
MMembrane
EEnvelope
NSNon-structural
ZVFZika Virus Fever
GBSGuillain-Barre Syndrome
ADEMAcute Disseminated Encephalomyelitis
EIPExtrinsic Incubation Period
SDSenatorial District
RDTRapid Diagnostic Test
AgAntigen
CIConfidence Interval
OROdds Ratio
ITNsInsecticide Treated Nets
χ2Chi Square

References

  1. Kindhauser, K.M.; Allen, T.; Frank, V.; Santhana, S.R.; Dye, C. Zika: The origin and spread of a mosquito-borne virus. Bull. World Health Organ. 2016, 94, 675–686. [Google Scholar] [CrossRef] [PubMed]
  2. Aubry, M.; Teissier, A.; Huart, M.; Merceron, S.; Vanhomwegen, J.; Roche, C.; Vial, A.; Teururai, S.; Sicard, S.; Paulous, S.; et al. Zika Virus Seroprevalence, French Polynesia, 2014–2015. Emerg. Infect Dis. 2017, 23, 669–672. [Google Scholar] [CrossRef]
  3. Noisumdaeng, P.; Dangsagul, D.; Sangsiriwut, K.; Prasertsopon, J.; Changsom, D.; Yoksan, S.; Ajawatanawong, P.; Buathong, R.; Puthavathana, P. Molecular characterization and geographical distribution of Zika virus worldwide from 1947 to 2022. Int. J. Infect. Dis. 2023, 133, 5–10. [Google Scholar] [CrossRef]
  4. Faye, O.; Faye, O.; Diallo, D.; Diallo, M.; Weidmann, M.; Sall, A.A. Quantitative real-time PCR detection of Zika virus and evaluation with field-caught Mosquitoes. Virol. J. 2013, 10, 311–318. [Google Scholar] [CrossRef] [PubMed]
  5. Lanciotti, R.S.; Lambert, A.J.; Holodniy, M.; Saavedra, S.; Signor Ldel, C. Phylogeny of Zika Virus in Western Hemisphere, 2015. Emerg. Infect Dis. 2016, 22, 933–935. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  6. Centres for Disease Control and Prevention. Clinical Signs and Symptoms of Zika Virus Disease. Available online: https://www.cdc.gov/zika/hcp/clinical-signs/index.html#:~:text=Characteristic%20clinical%20findings%20associated%20with,several%20days%20to%20a%20week (accessed on 15 May 2025).
  7. Hamel, R.; Liégeois, F.; Wichit, S.; Pompon, J.; Diop, F.; Talignani, L.; Missé, D. Zika virus: Epidemiology, clinical features and host-virus interactions. Microbes. Infect. 2016, 18, 441–449. [Google Scholar] [CrossRef]
  8. World Health Organization. Zika Virus Technical Report: Interim Risk Assessment WHO European Region. 2016. Available online: https://www.who.int/europe/publications/zika-virus-technical-report.-interim-risk-assessment-for-who-european-region (accessed on 23 May 2025).
  9. Rojas, D.P.; Dean, N.E.; Yang, Y.; Kenah, E.; Quintero, J.; Tomasi, S.; Ramirez, E.L.; Kelly, Y.; Castro, C.; Carrasquilla, G.; et al. The Epidemiology and Transmissibility of Zika Virus in Girardot and San Andres Island, Colombia, September 2015 to January 2016. Euro Surveill. 2016, 21, 30283. [Google Scholar] [CrossRef] [PubMed]
  10. Centers for Disease Control and Prevention (CDC). Zika Virus: Symptoms & Diagnosis. 2024. Available online: https://www.cdc.gov (accessed on 26 March 2025).
  11. Brito Ferreira, M.L.; Antunes de Brito, C.A.; Moreira, Á.J.P.; de Morais Machado, M.Í.; Henriques-Souza, A.; Cordeiro, M.T.; de Azevedo Marques, E.T.; Pena, L.J. Guillain-Barré Syndrome, Acute Disseminated Encephalomyelitis and Encephalitis Associated with Zika Virus Infection in Brazil: Detection of Viral RNA and Isolation of Virus during Late Infection. Am. J. Trop. Med. Hyg. 2017, 97, 1405–1409. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  12. World Health Organization (WHO). Zika Virus Fact Sheet. 2024. Available online: https://www.who.int (accessed on 26 March 2025).
  13. Weaver, S.C.; Costa, F.; Garcia-Blanco, M.A.; Ko, A.I.; Ribeiro, G.S.; Saade, G.; Vasilakis, N. Zika virus: History, emergence, biology, and prospects for control. Antivir. Res. 2016, 130, 69–80. [Google Scholar] [CrossRef]
  14. Musso, D.; Ko, A.I.; Baud, D. Zika Virus Infection-After the Pandemic. NEJM. 2019, 381, 1444–1457. [Google Scholar] [CrossRef]
  15. Ramos da Silva, S.; Gao, S. Zika Virus: An Update on Epidemiology, Pathology, Molecular Biology, and Animal Model. J. Med. Virol. 2016, 88, 1291–1296. [Google Scholar] [CrossRef] [PubMed]
  16. Ai, J.; Zhang, Y.; Zhang, W. Zika virus outbreak: ‘A perfect storm’. Emerg. Microbes Infect. 2016, 5, e21. [Google Scholar] [CrossRef] [PubMed]
  17. Dalvi, A.P.R.; Gibson, G.; Ramos, A.N., Jr.; Bloch, K.V.; Sousa, G.dS.; de Silva, T.L.N.; Braga, U.J.; Castro, C.M.; Werneck, L.G. Sociodemographic and environmental factors associated with dengue, Zika, and chikungunya among adolescents from two Brazilian capitals. PLoS Negl. Trop. Dis. 2023, 17, e0011197. [Google Scholar] [CrossRef]
  18. Qin, C.; Wang, Y.; Liu, M.; Liu, J. Global burden and incidence trends of zika virus infection among women aged 15–49 years from 2011 to 2021: A systematic analysis. J. Infect. Public Health 2024, 17, 102557. [Google Scholar] [CrossRef]
  19. Barzon, L.; Pacenti, M.; Berto, A.; Sinigaglia, A.; Franchin, E.; Lavezzo, E.; Brugnaro, P.; Palu, G. Isolation of Infectious Zika Virus from Saliva and Prolonged Viral RNA Shedding in a Traveller Returning from the Dominican Republic to Italy. Euro Surveill. 2016, 21, 30159. [Google Scholar] [CrossRef] [PubMed]
  20. Ioos, S.; Mallet, H.P.; Leparc Goffart, I.; Gauthier, V.; Cardoso, T.; Herida, M. Current Zika Virus Epidemiology and Recent Epidemics. Med. Mal. Infect. 2014, 44, 302–307. [Google Scholar] [CrossRef]
  21. Fagbami, A.H. Zika virus infections in Nigeria: Virological and Seroepidemiological Investigations in Oyo State. J. Hyg. 1978, 83, 213–219. [Google Scholar] [CrossRef]
  22. World Health Organization (WHO). World Malaria Report 2024. Lancet Microbe 2024, 6, 101073. Available online: https://www.thelancet.com/journals/lanmic/article/PIIS2666-5247(25)00001-1/fulltext (accessed on 26 March 2025).
  23. Pattanshetty, S.; Dsouza, V.S.; Shekharappa, A.; Yagantigari, M.; Raj, R.; Inamdar, A.; Alsamara, I.; Rajvanshi, H.; Brand, H. A Scoping Review on Malaria Prevention and Control Intervention in Fragile and Conflict-Affected States (FCAS): A Need for Renewed Focus to Enhance International Cooperation. J. Epidemiol. Glob. Health 2024, 14, 4–12. [Google Scholar] [CrossRef]
  24. ELmojtaba, I.M.; Al-Maqrashi, K.; Al-Musalhi, F.; Al-Salti, N. Optimal control and cost effectiveness analysis of a Zika–Malaria co-infection model. Partial. Differ. Equ. Appl. Math. 2024, 11, 100754. [Google Scholar] [CrossRef]
  25. Mac, P.A.; Kroeger, A.; Daehne, T.; Anyaike, C.; Velayudhan, R.; Panning, M. Zika, Flavivirus and Malaria Antibody Cocirculation in Nigeria. Trop. Med. Infect. Dis. 2023, 8, 171. [Google Scholar] [CrossRef] [PubMed]
  26. Baba, M.M.; Ahmed, A.; Jackson, S.Y.; Oderinde, B.S. Cryptic Zika virus infections unmasked from suspected malaria cases in Northeastern Nigeria. PLoS ONE 2023, 18, e0292350. [Google Scholar] [CrossRef] [PubMed]
  27. McKinney, K.L.; Wu, H.M.; Tan, K.R.; Gutman, J.R. Malaria in the pregnant traveler. J. Travel Med. 2020, 27, 4. [Google Scholar] [CrossRef] [PubMed]
  28. Adepoju, A.O.; Afinowi, A.O.; Tauheed, M.A.; Danazumi, U.A.; Dibba, B.S.L.; Balogun, B.J.; Flore, G.; Saidu, U.; Ibrahim, B.; Balogun, O.O.; et al. Multisectoral Perspectives on Global Warming and Vector-borne Diseases: A Focus on Southern Europe. Curr. Trop. Med. Rep. 2023, 10, 47–70. [Google Scholar] [CrossRef]
  29. Delrieu, M.; Martinet, J.-P.; O’Connor, O.; Viennet, E.; Menkes, C.; Burtet-Sarramegna, V.D.; Frentiu, F.; Dupont-Rouzeyrol, M. Temperature and transmission of chikungunya, dengue, and Zika viruses: A systematic review of experimental studies on Aedes aegypti and Aedes albopictus. Curr. Res. Parasitol. Vector-Borne Dis. 2023, 4, 100139. [Google Scholar] [CrossRef]
  30. Caminade, C.; McIntyre, K.M.; Jones, A.E. Impact of recent and future climate change on vector-borne diseases. Ann. N. Y. Acad. Sci. 2019, 1436, 157–173. [Google Scholar] [CrossRef]
  31. Mordecai, E.A.; Caldwell, J.M.; Grossman, M.K.; Lippi, C.A.; Johnson, L.R.; Neira, M.; Rohr, J.R.; Ryan, S.J.; Savage, V.; Shocket, M.S.; et al. Thermal biology of mosquito-borne disease. Ecol. Lett. 2019, 22, 1690–1708. [Google Scholar] [CrossRef]
  32. Stopard, I.J.; Sanou, A.; Suh, E.; Cator, L.J.; Thomas, M.B.; Guelbéogo, W.M.; Sagnon, N.; Lambert, B.; Churcher, T.S. Modelling the effects of diurnal temperature variation on malaria infection dynamics in mosquitoes. Commun. Biol. 2025, 8, 581. [Google Scholar] [CrossRef]
  33. Rocklöv, J.; Dubrow, R. Climate change: An enduring challenge for vector-borne disease prevention and control. Nat. Immunol. 2020, 21, 479–483. [Google Scholar] [CrossRef]
  34. Rabiu, I.; Musa, H.A.; Isaiah, Z.; Hussaini, M.; Umar, M.M.; Mustapha, S.; Abdullahi, J.I.; Shehu, A.; Sani, M.A. Dengue outbreaks in northern Nigeria: Evaluating the recommended Takeda vaccine and future prevention strategies. World J. Virol. 2024, 13, 95555. [Google Scholar] [CrossRef]
  35. Adesola, R.O.; Ajibade, F.A.; Idris, I.; Scott, G.Y.; Agaie, M.I. Addressing the Dengue fever challenges in Nigeria: A narrative review and recommendations for control. Infez. Med. 2024, 32, 157–167. [Google Scholar] [CrossRef] [PubMed]
  36. Onoja, B.A.; Oguzie, J.U.; George, U.E.; Asoh, K.E.; Ajayi, P.; Omofaye, T.F.; Igeleke, I.O.; Eromon, P.; Harouna, S.; Parker, E.; et al. Whole Genome Sequencing Unravels Cryptic Circulation of Divergent Dengue Virus Lineages in the Rainforest Region of Nigeria. Emerg. Microbes Infect. 2024, 13, 2307511. [Google Scholar] [CrossRef] [PubMed]
  37. Kaduna State City Population–Population Statistics, Charts, Maps and Location. Available online: https://citypopulation.de/en/nigeria/admin/NGA019__kaduna/ (accessed on 23 May 2025).
  38. Yayock, H.C.; Ndams, I.S.; Kogi, E.; Ahmed, A.B.; Vagime, C.G. Distribution of Mosquito Species in Kaduna Metropolis, Kaduna State, Northern Nigeria. Nig. J. Ent. 2015, 31, 137–145. Available online: https://www.esnjournal.com.ng/download/Vol_31/Vol_31_X23.pdf (accessed on 23 May 2025). [CrossRef]
  39. Centres for Disease Control and Prevention. Zika Virus Symptoms from Zika Virus. 2019. Available online: https://www.cdc.gov/zika/signs-symptoms/?CDC_AAref_Val=https://www.cdc.gov/zika/symptoms/index.html (accessed on 23 May 2025).
  40. Mathé, P.; Egah, D.Z.; Müller, J.A.; Shehu, N.Y.; Obishakin, E.T.; Shwe, D.D.; Pam, B.C.; Okolo, M.O.; Yilgwan, C.; Gomerep, S.S.; et al. Low Zika Virus seroprevalence among pregnant women in North Central Nigeria. J. Clin. Virol. 2018, 105, 35–40. [Google Scholar] [CrossRef]
  41. Babaniyi, A.O.; Mwaba, P.; Songolo, P.; Mazaba-Liwewe, L.M.; Mweene-Ndumba, I.; Masaninga, F.; Rudatsikira, E.; Siziya, S. Seroprevalence of Zika virus infection specific IgG in Western and North-Western Provinces of Zambia. Int. J. Public Health 2015, 4, 110–114. [Google Scholar]
  42. Otu, A.A.; Udoh, A.U.; Ita, I.O.; Hicks, P.J.; Ukpeh, I.; Walle, J. Prevalence of Zika and malaria in patients with fever in secondary healthcare facilities in south-eastern Nigeria. Trop. Doct. 2020, 50, 22–30. [Google Scholar] [CrossRef]
  43. Anejo-Okopi, J.; Gotom, D.Y.; Chiehiura, N.A.; Okojokwu, J.O.; Amanyi, D.O.; Egbere, J.O.; Adetunji, J.; Ujah, O.I.; Audu, O. The seroprevalence of zika virus infection among HIV positive and HIV negative pregnant women in Jos, Nigeria. Hosts Viruses 2020, 7, 129–136. [Google Scholar] [CrossRef]
  44. Ekesiobi, A.O.; Anene, C.C.; Nwigwe, H.C.; Emmy-Egbe, I.O.; Igbodika, M.C. Seasonal Distribution and Abundance of Yellow Fever Mosquito Vector, Aedes Aegypti, (Diptera: Culicidae) in Aguatu L.G.A. Anambra State, Nigeria. Chukwuemeka Odumegwu Ojukwu University. Int. Multidiscip. Res. J. 2014, 1, 25–32. [Google Scholar]
  45. Owusu-Asenso, C.M.; Mingle, J.A.A.; Weetman, D.; Afrane, Y.A. Spatiotemporal distribution and insecticide resistance status of Aedes aegypti in Ghana. Parasites Vectors 2022, 15, 61. [Google Scholar] [CrossRef]
  46. National Malaria Elimination Programme, Federal Ministry of Health: Malaria Indicator Survey 2015. Abuja 2016. Available online: https://nmcp.gov.ng (accessed on 17 May 2025).
  47. Bajoga, U.A.; Balarabe, H.S.; Olufemi, A.A.; Dalhat, M.M.; Sule, I.B.; Ibrahim, M.S.; Ajumobi, O.O. Trend of malaria cases in Kaduna State using routine surveillance data, 2011–2015. Pan Afr. Med. J. 2019, 32, 8. [Google Scholar] [CrossRef]
  48. Lozier, M.; Adams, L.; Febo, M.F.; Torres-Aponte, J.; Bello-Pagan, M.; Ryff, K.R.; Rivera-Garcia, B. Incidence of Zika Virus Disease by Age and Sex—Puerto Rico. Wkly. Rep. 2016, 65, 1219–1223. [Google Scholar] [CrossRef]
  49. Dos Santos, T.; Rodriguez, A.; Almiron, M.; Sanhueza, A.; Ramon, P.; de Oliveira, W.K.; Espinal, M.A. Zika Virus and the Guillain-Barré Syndrome—Case Series from Seven Countries. N. Engl. J. Med. 2016, 3, 1598–1601. [Google Scholar] [CrossRef] [PubMed]
  50. MacNamara, F.N. Zika virus: A report on three cases of human infection during an epidemic of jaundice in Nigeria. Trans. R. Soc. Trop. Med. Hyg. 1954, 48, 139–145. [Google Scholar] [CrossRef]
  51. Griffin, J.T.; Ferguson, N.M.; Ghani, A.C. Estimates of the changing age-burden of Plasmodium falciparum malaria disease in sub-Saharan Africa. Nat. Commun. 2014, 5, 3136. [Google Scholar] [CrossRef]
  52. Okunlola, O.A.; Oyeyemi, O.T. Spatio-temporal analysis of association between incidence of malaria and environmental predictors of malaria transmission in Nigeria. Sci. Rep. 2019, 9, 17500. [Google Scholar] [CrossRef] [PubMed]
  53. Diaz-Quijano, F.A.; Martínez-Vega, R.A.; Rodriguez-Morales, A.J.; Rojas-Calero, R.A.; Luna-González, M.L.; Díaz-Quijano, R.G. Association between the level of education and knowledge, attitudes and practices regarding dengue in the Caribbean region of Colombia. BMC Public Health 2018, 18, 143. [Google Scholar] [CrossRef] [PubMed]
  54. Nery, N.J.; Aguilar Ticona, J.P.; Gambrah, C.; Doss-Gollin, S.; Aromolaran, A.; Rastely-Júnior, V.; Costa, F. Social determinants associated with Zika virus infection in pregnant women. PLoS Negl. Trop. Dis. 2021, 15, e0009612. [Google Scholar] [CrossRef]
  55. Maharajan, M.K.; Rajiah, K.; Belotindos, J.A.S.; Basa, M.S. Social Determinants Predicting the Knowledge, Attitudes, and Practices of Women Toward Zika Virus Infection. Front. Public Health 2020, 8, 170. [Google Scholar] [CrossRef]
  56. Bearcroft, W.G. Zika virus infection experimentally induced in a human volunteer. Trans. R. Soc. Trop. Med. Hyg. 1956, 50, 442–448. [Google Scholar] [CrossRef]
  57. Duffy, M.R.; Chen, T.H.; Hancock, W.T.; Powers, A.M.; Kool, J.L.; Lanciotti, R.S.; Hayes, E.B. Zika virus outbreak on Yap Island, Federated States of Micronesia. N. Engl. J. Med. 2009, 360, 2536–2543. [Google Scholar] [CrossRef]
  58. Plourde, A.R.; Bloch, E.M. A Literature Review of Zika Virus. Emerg. Infect. Dis. 2016, 22, 1185–1192. [Google Scholar] [CrossRef] [PubMed]
  59. Wimalasiri-Yapa, B.M.C.R.; Yapa, H.E.; Huang, X.; Hafner, L.M.; Kenna, T.J.; Frentiu, F.D. Zika Virus and Arthritis/Arthralgia: A Systematic Review and Meta-Analysis. Viruses 2020, 12, 1137. [Google Scholar] [CrossRef] [PubMed]
  60. World Health Organization. Malaria World Report. 2023. Available online: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2023 (accessed on 12 May 2025).
  61. Oyefolu, A.O.B.; Shaibu, O.J.; Anjorin, A.A.; Akinyemi, O.K. A Review on The State of Zika Virus in Nigeria. J. Res. Rev. Sci. 2019, 6, 41–47. [Google Scholar] [CrossRef] [PubMed]
  62. Jeong, Y.E.; Cha, G.W.; Cho, J.E.; Lee, E.J.; Jee, Y.; Lee, W.J. Viral and serological kinetics in Zika virus-infected patients in South Korea. Virol. J. 2017, 14, 70. [Google Scholar] [CrossRef]
Microbiolres 16 00109 g001
Figure 1. Seroprevalence rates of Zika virus antibodies and P. falciparum Ag among febrile patients in Kaduna State, Nigeria.
Figure 1. Seroprevalence rates of Zika virus antibodies and P. falciparum Ag among febrile patients in Kaduna State, Nigeria.
Microbiolres 16 00109 g001
Microbiolres 16 00109 g002
Figure 2. Co-infection of ZV seromarkers and Malaria among febrile patients in Kaduna State.
Figure 2. Co-infection of ZV seromarkers and Malaria among febrile patients in Kaduna State.
Microbiolres 16 00109 g002
Microbiolres 16 00109 g003
Figure 3. (A–C) Map of Kaduna State highlighting LGAs with Zika and malaria hotspots: (A) highest ZV-IgM, (B) highest ZV-IgG, and (C) highest P. falciparum antigen.
Figure 3. (A–C) Map of Kaduna State highlighting LGAs with Zika and malaria hotspots: (A) highest ZV-IgM, (B) highest ZV-IgG, and (C) highest P. falciparum antigen.
Microbiolres 16 00109 g003
Table 1. Seroprevalence of ZV seromarkers and malaria in relation to marital status among febrile patients in Kaduna State, Nigeria.
Table 1. Seroprevalence of ZV seromarkers and malaria in relation to marital status among febrile patients in Kaduna State, Nigeria.
Marital StatusNo. of SamplesZV IgMZV IgGMalaria
No + ve (%)p Value/χ2No + ve (%)p Value/χ2No + ve (%)p Value/χ2
Married27113 (4.8)0.879/0.24730 (11.1)0.023/7.53517 (6.3)0.011/9.023
Single1466 (4.1)5 (3.4)22 (15.1)
Divorced30 (0.0) 0 (0.0) 0 (0.0)
Total 42019 (8.9) 35 (14.5) 39 (21.4)
No + ve = Number positive; χ2 = Chi square.
Table 2. Age distribution of ZV seromarkers and malaria among febrile patients in Kaduna State, Nigeria.
Table 2. Age distribution of ZV seromarkers and malaria among febrile patients in Kaduna State, Nigeria.
Age (Years)No. of SamplesZV IgMZV IgGMalaria
No + ve (%)p Value/χ2No + ve (%)p Value/χ2No + ve (%)p Value/χ2
1–10491 (2.0)0.834/2.110 1 (2.0)0.004/17.4189 (18.4)0.008/15.656
11–20693 (4.3)3 (4.3)10 (14.5)
21–301147 (6.1) 10 (8.8) 12 (10.5)
31–40734 (5.5) 4 (5.5) 4 (5.5)
41–50451 (2.2) 3 (6.7) 4 (8.9)
>50703 (4.3) 14 (20.0) 0 (0.0)
Total42019 (24.4) 34 (47.3) 39 (57.8)
No + ve = Number positive; χ2 = Chi square
Table 3. Prevalence of ZV and malaria by lgas in Kaduna State, Nigeria.
Table 3. Prevalence of ZV and malaria by lgas in Kaduna State, Nigeria.
VariablesNo of SamplesZaria +ve (%)Chikun + ve (%)Lere + ve (%)Sanga + ve (%)Kachia + ve (%)K/South + ve (%)p Value/χ2
ZV IgM703 (4.3)3 (4.3)7 (10.0)1 (1.4)2 (2.9)3 (4.3)0.220/
6.891
ZV IgG702 (2.9)6 (8.6)6 (8.6)6 (8.6)10 (14.3)5 (7.1)0.292/
6.140
Malaria7013 (18.6)7 (10.0)6 (8.6)4 (5.7)6 (8.6)3 (4.3)0.0639/
10.430
+ve = Number positive; χ2 = Chi square.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Atai, R.B.; Aminu, M.; Ella, E.E.; Kia, G.S.N.; Obishakin, E.T.; Luka, H.G.; Joel, G.S.; Onoja, A.B. Zika Virus in Malaria-Endemic Populations: A Climate Change-Driven Syndemic in the Sudan Savannah, Nigeria. Microbiol. Res. 2025, 16, 109. https://doi.org/10.3390/microbiolres16060109

AMA Style

Atai RB, Aminu M, Ella EE, Kia GSN, Obishakin ET, Luka HG, Joel GS, Onoja AB. Zika Virus in Malaria-Endemic Populations: A Climate Change-Driven Syndemic in the Sudan Savannah, Nigeria. Microbiology Research. 2025; 16(6):109. https://doi.org/10.3390/microbiolres16060109

Chicago/Turabian Style

Atai, Rebecca B., Maryam Aminu, Elijah E. Ella, Grace S. N. Kia, Emmanuel T. Obishakin, Helen G. Luka, Ganih S. Joel, and Anyebe B. Onoja. 2025. "Zika Virus in Malaria-Endemic Populations: A Climate Change-Driven Syndemic in the Sudan Savannah, Nigeria" Microbiology Research 16, no. 6: 109. https://doi.org/10.3390/microbiolres16060109

APA Style

Atai, R. B., Aminu, M., Ella, E. E., Kia, G. S. N., Obishakin, E. T., Luka, H. G., Joel, G. S., & Onoja, A. B. (2025). Zika Virus in Malaria-Endemic Populations: A Climate Change-Driven Syndemic in the Sudan Savannah, Nigeria. Microbiology Research, 16(6), 109. https://doi.org/10.3390/microbiolres16060109

Article Metrics

Back to TopTop