AIDAdvances in Infectious Diseases2164-2648Scientific Research Publishing10.4236/aid.2024.142031AID-133680ArticlesMedicine&Healthcare Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Coinfection with Malaria in Selected States in Nigeria OluwagbemigaOlanrewaju Aina1OlufemiSamuel Amoo2KazeemAdewale Osuolale3AdewaleKayode Ojogbede4AzukaPatrick Okwuraiwe2DavidAyoola Oladele5AdesolaZaidat Musa3TajudeenAkanji Bamidele6CelestinaOnyinye Okoyenta1AbideenOlurotimi Salako5ToyosiYekeen Raheem6IfeomaEugenia Idigbe5FehintolaAnthonia Ige2JosephOjonugwa Shaibu2GregoryAigbe Ohihoin5KikelomoWright7BisolaAdebayo7HusseinAbdu-Razzaq8AbdulrahmanAhmad9MustaphaImam10BashirBello Tambuwal11MuhammadShuaibu Gobir9RichardIkwuogu12ChristianTetsola12GloriaPatrick-Ferife12NathanielEnamuotor12MildredOkowa12WilliamNwachukwu13CorneliusOhonsi13MagdaleneEgede13ChinweOchu13EhimarioIgumbor14OliverChukwujekwu Ezechi5BabatundeLawal Salako5RosemaryAjuma Audu2Department of Community Health & Primary Health Care, Lagos State University College of Medicine, Lagos State University Teaching Hospital, Lagos, NigeriaBiochemistry and Nutrition Department, Nigerian Institute of Medical Research, Lagos, NigeriaClinical Sciences Department, Nigerian Institute of Medical Research, Lagos, NigeriaSokoto State Ministry of Health, Sokoto, NigeriaPublic Health and Epidemiology Department, Nigerian Institute of Medical Research, Lagos, NigeriaResearch Unit, Lagos State Ministry of Health, Lagos, NigeriaCenter for Infectious Disease Research, Nigerian Institute of Medical Research, Lagos, NigeriaMonitoring and Evaluation Unit, Nigerian Institute of Medical Research, Lagos, NigeriaDepartment of Medical Biochemistry Usmanu Danfodiyo University, Sokoto, NigeriaDelta State Ministry of Health, Asaba, NigeriaMolecular Biology and Biotechnology Department, Nigerian Institute of Medical Research, Lagos, NigeriaNigeria Centre for Disease Control, Abuja, NigeriaCentre for Advanced Medical Research and Training Usmanu Danfodiyo University, Sokoto, NigeriaCentre for Human Virology and Genomics, Microbiology Department, Nigerian Institute of Medical Research, Lagos, Nigeria250420241402442455 8, February 2024 2024 1, 2024 4, © Copyright 2014 by authors and Scientific Research Publishing Inc. 2014This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and <i>Pla</i><i>s</i><i>modium</i><i> </i><i>species</i> are the causative agents of coronavirus disease 2019 (COVID-19) and malaria respectively with similar clinical presentations. The objective of this study is to determine the burden of co-infection of SARS-CoV-2 and malaria in the general population. Five (5 mLs) of blood samples were collected for SARS-CoV-2 and malaria parasite test. The malaria test was performed using a commercially available one-step malaria antigen <i>Plasmodium</i><i> </i><i>falciparum</i> histidine-rich protein 2 (Pf HRP-II) rapid test kit. The results of the study showed that the participants that were coinfected with SARS-CoV-2 IgG and malaria were 13 (2.5%) in Lagos, 1114 (39.1%) in Delta and 49 (2.3%) in Sokoto States. The prevalence of coinfection of SARS-CoV-2 and malaria in urban areas in Lagos, Delta and Sokoto States were 7 (2.2%), 1373 (48.1%), and 5 (0.2%) respectively. In rural areas, the prevalence of coinfection of SARS-CoV-2 and malaria in Lagos, Delta and Sokoto States were 6 (0.3%), 365 (12.8%), and 44 (2.1%) respectively in this study. This suggests that participants in the urban areas were more prone to co-infections than the rural areas in Lagos and Delta states, while it was otherwise in Sokoto State. In conclusion, the co-infection of SARS-CoV-2 and malaria was very high in Delta State compared to the other States. It is important for clinics to screen for both diseases when patients present with symptoms of malaria. This is because the infections have similar symptoms and the public is quick to assume malaria infection without diagnosing for COVID-19 and vice versa.

SARS-CoV-2 Malaria Coinfection1. Introduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Plasmodium spp. are pathogenic microorganisms that cause coronavirus disease 2019 (COVID-19) and malaria respectively [1] [2] . Infectious diseases are among the leading causes of death worldwide [3] . Even though SARS-CoV-2 and malaria parasites differ a lot in classification, being that the former is a virus and the latter a parasite, they present similar symptoms such as fever, dry cough, and malaise in infected individuals [4] [5] [6] . SARS-CoV-2 also responds to existing antimalarial drugs such as chloroquine in combination with other therapeutics [4] [7] [8] . Due to the similarities in the epidemiology of these infectious diseases, misdiagnosis and/or cross-immunity can exist in people infected with SARS-CoV-2 or malaria parasites, especially in countries with limited resources and those endemic to malaria parasites [5] [7] . Therefore, the official data on the prevalence of SARS-CoV-2 alone may not be a true reflection of the current burden of COVID-19 disease [5] [6] . In addition, antibodies against SARS-CoV-2 provide more detailed information on possible infection with SARS-CoV-2 within a population [9] . The reason is that anti-SARS-CoV-2 IgG is normally produced in individuals who have a symptomatic or asymptomatic SARS-CoV-2 viral infection. Information on the prevalence of SARS-CoV-2, anti-SARS-CoV-2 IgG and malaria parasites in Lagos, Delta and Sokoto States will provide a broader estimate of the burden of SARS-CoV-2 IgG and malaria parasites in these states and also guide public health policies in the fight against these infectious diseases. The prevalence of SARS-CoV-2 IgG, malaria parasite and their coinfections will be discussed here.

As of January 11th 2024 the global prevalence of SARS-CoV-2 was 701,508,817 confirmed cases with about 6,966,767 deaths reported to the World Health Organization [10] . In Africa, the prevalence was 9,568,942 confirmed cases and over 175,477 deaths. Nigeria has a prevalence record of 267,173 confirmed cases and 3155 deaths reported to the World Health Organization as of 11th January, 2024 [10] .

The prevalence of SARS-CoV-2 in Lagos State as of 4th April 2022 was 99,226 confirmed cases and 769 deaths, Delta State had 5717 confirmed cases and 111 deaths, and Sokoto had 817 confirmed cases and 28 deaths [11] . According to the Nigerian Centre for Disease Control (NCDC) and Nigerian Institute of Medical Research (NIMR) SARS-CoV-2 antibody survey, the prevalence of SARS-CoV-2 antibodies in households in Lagos State was 23.3% (95% Cl 20.3 - 26.0), 36.8% (95% Cl 32.8 - 41.0) in Delta State, and 65.3% (95% Cl 38.3 - 71.7) in Sokoto State [12] . The study also stated that the seroprevalence of anti-SARS-CoV-2 is higher than the prevalence rate of COVID-19 disease that was detected by SARS-CoV-2 surveillance within Lagos, Delta and Sokoto States populations [12] .

Malaria is a life-threatening public health parasitic disease. There were an estimated 247 million malaria cases and 619,000 deaths due to malaria in 2021 (WHO, 2021). About two-thirds (47,000) of the additional malaria deaths were due to disruptions in the provision of malaria prevention, diagnosis and treatment during the pandemic (WHO, 2021). The prevalence of malaria parasites in children under the age of 5 years in States was 3%, 10% and 36% in Lagos, Delta and Sokoto States respectively [13] . The prevalence of malaria has drastically decreased especially in urban areas. This could be due to different malaria control intervention programmes by the Government in urban areas [14] .

Early in the COVID-19 pandemic, WHO projected a possible doubling of deaths in 2020 in sub-Saharan Africa. The strenuous efforts of malaria-endemic countries and their partners to maintain malaria services during the pandemic averted this worst-case scenario [15] . Many countries experienced disruptions to malaria prevention, diagnosis and treatment. In sub-Saharan Africa, there was an estimated 12% increase in malaria deaths in 2020 over 2019. This highlights the consequences of even moderate service disruptions to malaria services in a population at risk [15] .

There was therefore a need to conduct a population-based study incorporating regions with a high and low burden of the disease as well as rural and urban settings. Hence, our study aimed at determining the co-infection of SARS-CoV-2 with malaria in the general population.

The role of asymptomatic and pre-symptomatic individuals in transmission of SARS-CoV-2 and malaria co-infection was determined. This is useful in estimating the disease burden and revealing symptom-free infected individuals with SARS-CoV-2 and malaria. This survey also served as an epidemiological platform that screened participants for COVID-19-related co-morbidities including malaria. The study determined the prevalence of asymptomatic SARS-CoV-2 co-infection with malaria, characterized disease patterns and transmission dynamics in a large population and determined association with comorbidities in a high-prevalence setting. The objective of this study is to estimate the burden of co-infection of SARS-CoV-2 and malaria in Lagos, Delta and Sokoto States, Nigeria.

2. Methods2.1. Study Design and Settings

This was a household cross-sectional study of COVID-19 coinfection with malaria. The study was conducted in Lagos, Sokoto and Delta States in Nigeria. Lagos is located in the southwest of Nigeria. It is the most populous state in the country. Sokoto is located in the extreme northwest of the country, bounded by the Republic of Niger, Nasarawa and Kebbi States. Delta State is located in the south-south geopolitical zone of the country. The study period was October 2020 for Lagos State, March 2021 for Sokoto State and July 2021 for Delta State.

2.2. Study Population and Site

The study population consisted of all members of the household, irrespective of age. Clinical data and biological specimens were collected from study participants who consented.

Inclusion criteria: All persons living in the household including children were invited to participate in the study.

Exclusion criteria: Household members who were in residential institutions, such as boarding schools, hostels, dormitories, or prisons were excluded. Household members who refused to give informed consent, or contraindication to venipuncture were also excluded.

2.3. Sample Size Determination and Sampling Procedure

The overall sample size was determined by the number of blood draws needed to obtain relatively robust estimates of SARS-CoV-2 seroprevalence for each stratum (states). Urban EAs (enumeration areas) were oversampled in the two predominantly rural states to yield more precise estimates for the urban and rural strata within each state, state-level prevalence was the primary determinant of sample size. Thirty-four EAs were sampled per state, with 20 households sampled per EA in Sokoto and Delta State, while 30 EAs were sampled in Lagos State with 20 households because of higher prevalence in Lagos State during the pandemic. The sample size table (Table 1) took into account assumptions on relative standard error (RSE), which is the standard error of the survey point estimate divided by the point estimate), an assumed 68% response rate, and estimated design effect, all at 95% confidence intervals (CI). The estimated RSEs

Sample size
State*EAs*Num of HH per EATotal HHsAve. HH SizeTotal Sample size
Lagos302060042400
Sokoto34206805.33604
Delta34206804.53060

*EAs: Enumeration Areas, *Num HH: Numbers of Households.

and 95% CIs take into account adjustments for non-response, number of individuals per household, individual non-response, and refusal of blood testing or specimen loss.

2.4. Data Collection

Study-related information, including demographic characteristics, clinical information, and exposure information, was collected by a trained research assistant using an electronic data collection tool (REDCap) and hard copies of the data collection tool as backup.

2.5. Specimen Collection and Transport

Five milliliters of venous blood was collected from each participant into a plain vacutainer bottle. At the study locations, blood samples were examined for malaria using the commercially available one-step malaria antigen Plasmodium falciparum (HRP-II) rapid diagnostic test (RDT) kit, performed according to the manufacturer’s instructions. Briefly, 5 microliters of whole blood samples were transferred into the specimen well, the assay diluent (4 drops) was added. The test kit was left for 15 minutes after which the results were read and collated. Individuals who tested positive were administered antimalarials by the study physician according to standard prescriptions. The remaining blood samples were transported in ice packs to the state satellite laboratories, centrifuged and the sera collected into clean cryovials. The serum samples were stored at −20˚C and shipped to the Center for Human Virology and Genomics, at the Nigerian Institute of Medical Research for further analysis.

2.6. Laboratory Evaluations

Laboratory and infection prevention and control precautions for COVID-19 were observed according to the WHO guidelines.

2.7. Serological Testing

Serum samples were screened for the presence of SARS-COV2 antibodies using Luminex xMAP SARS-CoV-2 Multi-Antigen IgG Assay (multiplexed microsphere-based assay), which targets the nucleocapsid protein, spike protein, and the receptor-binding domain of SARS-CoV-2. The test was carried out according to the manufacturer’s instructions.

2.8. Statistical Analyses

Descriptive statistics, such as frequencies and percentages, were used to present the households in Lagos, Sokoto and Delta states and the prevalence of SARS-CoV-2 antibody coinfection with malaria across different demographic and clinical variables. The measures include counts of households selected, not found/destroyed, vacant, occupied, and those that refused to participate as well as the number and percentage of individuals with SARS-CoV-2 only, malaria only, coinfection, and those not infected. Weighted analysis was used to ensure it is representative of the population (Tables 1-4). The data were analyzed using standard STATA 16.0 statistical software. Post-stratification weights were derived for each state using the age-sex distribution from the state-level projection for 2020, based on the 2006 census data. The presented percentages were weighted unless otherwise noted. Wealth quintiles were created using principal component analysis (PCA) methods from the Demographic and Health Surveys. PCA was run for Lagos, Sokoto, and Delta States separately. All household assets (e.g. electricity, radio, television, vehicle), floor material, wall material, primary cooking fuel source, toilet facilities (with the exception of other toilets due to low frequency), and number of household members per sleeping space were included in the wealth index.

2.9. Ethical Approval and Informed Consent

Ethical approval was obtained from the National Health Research Ethics Committee (NHREC/01/01/2007-02/05/2022), NIMR-IRB and the respective states’ ethical committees. Social approvals were also obtained from different states. Written Informed consent was obtained from all individuals who participated and only consenting participants had blood samples collected for biological testing by trained phlebotomists. Assent was obtained from all children aged 7 to 17 years before their participation in the study, while consent for children under the legal age of consent was also obtained from a parent or legal guardian.

3. Results

The overall prevalence of SARS-CoV-2 IgG, malaria positivity and in co-infected with SARS-CoV-2 IgG and malaria in this study were 29.8%, 25% and 11.2% respectively.

The participants that had only SARS-CoV-2 IgG were 546 (40.8%) in Lagos, 1216 (58.1%) in Sokoto and 902 (31.1%) in Delta States. Those that were positive for malaria parasites were 54 (7.8%), 574 (27.4%) and 515 (18.1%) participants in Lagos, Sokoto and Delta States respectively. The participants who were co-infected with SARS-CoV-2 IgG and malaria were 13 (2.5%) in Lagos (Table 2), 49 (2.3%) in Sokoto State (Table 3), and 1738 (60.9%) in Delta State (Table 4).

In the urban area of Lagos State, the participants who were co-infected with SARS-CoV-2 (IgG and malaria were 7 (2.2%) while in the rural area, they were 6 (0.3%). Only 10 males and 3 females were co-infected with SARS-CoV-2 and

SARS-CoV-2 antibody coinfection with malaria by selected demographic and clinical variables in Lagos
CharacteristicsSARS-CoV-2β only (N=546)Malaria Positive only N=(54)Co-infection (N = 13)Not infected with either (N = 1774)
n%αN%n%n%
Residence
Urban49223.6321.772.223974.7
Rural5417.2226.160.3153574.3
Gender
Males24023.0252.5100.973373.7
Females30622.5292.330.3104175.0
Age groups**
Children9919.2143.240.837676.7
Adolescents and young adults11027.8153.641.027067.6
Adults30123.3221.640.399474.7
Senior adults3621.531.410.813476.4
Wealth quintile
Lowest9620.3143.020.435476.3
Second9920.2142.920.436076.6
Middle12626.7101.951.232770.3
Fourth10022.291.920.636074.9
Highest12524.371.820.437373.6
Comorbidities/Pre-existent conditions
Currently Pregnant819.922.100.04278.0
Diabetes00.000.000.06100.0
Hypertension724.400.000.02475.7
Heart disease119.700.000.0480.3
Asthma470.700.000.0229.3
Tuberculosis
Chronic kidney disease
Emphysema/Chronic bronchitis/COPD130.600.000.0169.4
HIV00.000.000.000.0
Sickle cell disease222.700.000.0977.3
Cancer
Others
No reported comorbidity49023.1452.2130.7155274.0
1 co-morbidity1921.520.700.08377.8
2 or more comorbidities241.300.000.0458.7
Symptomatology*
Symptomatic7817.1245.520.434677.0
Asymptomatic45724.2291.5110.7138273.7

*at least one symptom reported since March 2020. **Children defined as less than 10, Adolescents and young adults defined as 10 - 17 years old, adults defined as 18 - 64 years old, and senior adults defined as 65 and over. α All percentages are weighted.

SARS-CoV-2 antibody coinfection with malaria by selected demographic and clinical variables in Sokoto
CharacteristicsSARS-CoV-2β only (N = 1216)Malaria Positive only (N = 574)Co-Infection (N = 49)Not infected with either (N = 2048)
n%αN%n%n%
Residence
Urban23411.2361.750.241619.8
Rural98246.953825.7442.1163277.8
Gender
Males75936.336717.5321.5127860.9
Females45721.92079.9170.8770
Age groups**
Children34216.41718.290.456326.9
Adolescents and young adults22810.91145.4120.641719.9
Adults60128.726312.6241.199747.5
Senior adults452.2262.240.2713.4
Wealth quintile
Lowest25512.21235.9160.841619.9
Second24211.61014.8130.640319.2
Middle24611.81014.830.141419.8
Fourth25412.21115.3120.643020.5
Highest21910.51386.550.238418.3
Comorbidities/Pre-existent conditions
Currently Pregnant110.680.340.2170.9
Diabetes160.890.400.0271.3
Hypertension211.0120.600.0440.2
Heart disease10.00100.000.020.1
Asthma30.0110.0100.050.2
Tuberculosis10.00100.000.010.1
Chronic kidney disease00.000.000.000.0
Emphysema/Chronic bronchitis/COPD00.000.000.000.0
HIV00.000.000.000.0
Sickle cell disease301.4150.700.0693.2
Cancer954.5472.200.01326.4
Others160.870.32712.900.0
No reported comorbidity
1 co-morbidity
2 or more comorbidities
Symptomatology*
Symptomatic103249.348823.300.0874.2
Asymptomatic462.2190.9472.2169981.0

α All percentages are weighted.

SARS-CoV-2 antibody coinfection with malaria by selected demographic and clinical variables in Delta
CharacteristicsSARS-CoV-2β only (N = 902)Malaria Positive only (N = 515)Co-infection (N = 1738)Not infected with either (N = 1114)
n%αN%n%n%
Residence
Urban71024.929110.2137348.176326.8
Rural1926.72247.936512.835112.3
Gender
Males37713.22629.275226.446716.4
Females52518.42538.998634.664722.7
Age groups**
Children1615.71445.144515.61946.8
Adolescents and young adults16017.31244.434912.21455.1
Adults51918.22207.784629.764922.8
Senior adults622.2271.0983.41264.4
Wealth quintile
Lowest1635.71354.736112.72207.7
Second1896.61194.231711.12528.8
Middle1986.91073.833811.92278.0
Fourth1786.2802.835512.52177.6
Highest1746.1742.636712.91986.9
Comorbidities/Pre-existent conditions
Currently Pregnant80.360.2230.880.3
Diabetes130.530.160.2271.0
Hypertension180.670.3110.4431.5
Heart disease10.010.00030.1
Asthma0010.030.120.1
Tuberculosis000010.000.0
Chronic kidney disease00000000
Emphysema/Chronic bronchitis/COPD00000000
HIV00000000
Sickle cell disease331.2180.6291.0551.9
Cancer82528.947516.7164757.897134.1
Others110.480.3210.7230.8
No reported comorbidity
1 co-morbidity
2 or more comorbidities
Symptomatology*
Symptomatic293.22110.4391.4481.7
Asymptomatic70578.241414.5150552.876126.7

malaria in Lagos State. The participants who were co-infected with SARS-CoV-2 and malaria in urban area were 5 (0.2%) while in the rural areas they were 44 (2.1%). The male participants were 32 (1.5%) and female participants were 17 (0.8) in Sokoto State. In Delta State, the participants who were co-infected with SARS-CoV-2 and malaria in the urban area were 1373 (48.1%), while in the rural area they were 365 (12.8%). Male and female participants who were co-infected with SARS-CoV-2 and malaria were 752 (26.4%) and 986 (34.6%) respectively.

The children, adolescents and young adults who were co-infected with SARS-CoV-2 and malaria in Lagos State were 4 (0.8%), 4 (1.0%), and 5 (1.1%) respectively. In Sokoto State, the children, adolescents and young adults co-infected with SARS-CoV-2 and malaria were 9 (0.4%), 12 (0.6%) and 28 (1.3%) respectively. The children, adolescents, and young adults who were co-infected with SARS-CoV-2 and malaria in Delta State were 445 (15.6%), 349 (12.2%), and 944 (33.1%) respectively.

In Lagos, 2 (0.4%) of symptomatic participants had SARS-CoV-2 antibodies and in malaria, 17% had only SARS-CoV-2 antibodies. While 5.5% had malaria only. In Sokoto state, no symptomatic participant had co-infection of SARS-CoV-2 antibodies and malaria, but asymptomatic participants with co-infections were 47 (2.2%). Symptomatic individuals that had only SARS-CoV-2 antibodies or malaria were 1032 (49.3%) and 488 (23.4%) respectively. In Delta state, 39 (1.4%) of symptomatic participants had co-infections with SARS-CoV-2 antibodies and malaria; 29 (7.5%) of the symptomatic individuals had only SARS-CoV-2 antibodies, while those with only malaria were 11 (0.4%).

There were no comorbidities/pre-existent conditions among the participants in Lagos and Sokoto States with coinfection but the wealth quintile is the highest in the middle class 5 (1.2%) in Lagos State and it is high in the lowest class 16 (0.8%) in Sokoto State. The comorbidities/pre-existent conditions that were observed among the participants in Delta State were diabetes, hypertension and asthma 20 (0.7%), and cancer 1647 (57.8%) while the wealth quintile was observed in the highest class 367 (12.1%).

4. Discussion

Co-infection of SARS-CoV-2 and malaria was first reported in China [16] . Other authors have also reported it in Nigeria [17] [18] , Burkina Faso [19] , Sudan [20] and India [21] . The symptoms of SARS-CoV-2 and malaria are overlapping [22] , leading many people to assume they have a malaria infection when they actually have SARS-CoV-2 [5] . The only way to differentiate between the illnesses is by conducting malaria and SARS-CoV-2 tests. This study showed that co-infection of SARS-CoV-2 and malaria in the participants was common.

This co-infection could be attributed to many factors, including warm weather, lack of proper diagnosis, previous infection with malaria, and the use of antimalarial medicine. Additionally, population genetics appears to play a significant role in shaping the COVID-19 dynamics [23] . This is evident from recent genomic screening analyses of the angiotensin-converting enzyme 2 (ACE2) and malaria-associated-variants, which identified 6 candidate genes that might play a role in malaria and COVID-19 incidence and severity [24] .

This study showed the co-infection of SARS-CoV-2 and malaria in three states in Nigeria, where SARS-CoV-2 was tested. The lowest co-infection of SARS-CoV-2 and malaria was in Lagos state. This low frequency of SARS-CoV-2 and malaria co-infections found in our study in Lagos State has also been reported in other studies [17] [24] [25] [26] . The highest co-infection was in Delta State. Even though the exact cause of the observed epidemiological heterogeneity of co-infection of SARS-CoV-2 and malaria amongst the states in Nigeria is unknown, the high rate of SARS-CoV-2 and malaria co-infection in Delta State may be attributed to the presence of pre-existing conditions/co-morbidities like cancer which was observed to be highly prevalent (1647 (57.8%)) among the co-infected participants in Delta State. The immunological mechanisms by which individuals acquire protective immunity or suffer co-infections and comorbidities in Africa are largely unknown [27] . Some factors such as demographics, climate, environment, host genetics, social factors, adherence to public policies/guidelines and others have been suggested to influence co-infection dynamics in Africa [27] .

The prevalence of co-infection of SARS-CoV-2 and malaria in the rural area was observed to be higher in Lagos and Sokoto states in this study than in the urban areas. Only Delta state had a reverse prevalence. The adults had the highest co-infection of SARS-CoV-2 and malaria than the children in both Delta and Sokoto States, this corroborates the study carried out in Burkina Faso [19] .

As for the symptomatology of coinfections, Delta State had the highest burden of asymptomatic participants among the States, while Lagos had the lowest number of asymptomatic participants. Generally, the study showed few participants with symptoms of SARS-CoV-2 and malaria parasite co-infection. Some authors suggested that patients with SARS-CoV-2 and malaria did not seem to have a worse disease outcome but previous malaria exposure appears to be related to lower frequency of severe COVID-19 [28] . Another study reports that patients co-infected with malaria had a significantly faster recovery compared to those not co-infected [21] . The public health importance of this study is that the coinfection of malaria and COVID-19 in some people may be misdiagnosed and the late diagnosis and differentiation of these two diseases from each other can increase the mortality and complications they cause.

This study showed that there were no comorbidities/pre-existent conditions among the participants in Lagos and Sokoto States with coinfection of malaria and COVID-19 but the wealth quintile is the highest in the middle class in Lagos State while it is high in the lowest class in Sokoto State. When compared to Delta State, the comorbidities/pre-existent conditions that were observed among the participants were diabetes, hypertension, asthma and cancer while the wealth quintile was observed in the highest class. This is similar to the study carried out by another author [29] , which says wealthier people, particularly people from the fourth and highest wealth quintiles, should be careful to avoid unhealthy lifestyles to prevent hypertension, diabetes and cancer.

The limitation of this study was that only RDT kits were used to test the participants for malaria infection and not microscopy. The RDT kits detect both current and old malaria infections due to the antigen-based nature of the RDT.

5. Conclusion

Co-infection of SARS-CoV-2 IgG and malaria was very high in Delta State compared to the other States. The participants in the urban area were more prone to co-infection than the rural area in Delta state only. It is important for clinics to conduct malaria screening to detect possible cases as soon as possible and avoid possible missed diagnoses of COVID-19 co-infections. The infections have similar symptoms and the public is quick to assume they have malaria.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

Cite this paper

Aina, O.O., Amoo, O.S., Osuolale, K.A., Ojogbede, A.K., Okwuraiwe, A.P., Oladele, D.A., Musa, A.Z., Bamidele, T.A., Okoyenta, C.O., Salako, A.O., Raheem, T.Y., Idigbe, I.E., Ige, F.A., Shaibu, J.O., Ohihoin, G.A., Wright, K., Adebayo, B., Abdu-Razzaq, H., Ahmad, A., Imam, M., Tambuwal, B.B., Gobir, M.S., Ikwuogu, R., Tetsola, C., Patrick-Ferife, G., Enamuotor, N., Okowa, M., Nwachukwu, W., Ohonsi, C., Egede, M., Ochu, C., Igumbor, E., Ezechi, O.C., Salako, B.L. and Audu, R.A. (2024) Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Coinfection with Malaria in Selected States in Nigeria. Advances in Infectious Diseases, 14, 442-455. https://doi.org/10.4236/aid.2024.142031

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