Ethical approval was obtained from Ebonyi State Ministry of Health (Approval no. SMOH/03/017). The approval letter from the State Ministry of Health were taken to the traditional rulers as well as community leaders of the study communities for their approval of the study in their respective communities. Following approval by the community leaders, informed consent of the participants was sort through community mobilization and sensitization. The community members were invited to their town hall through the help of the community leaders, where they were explained the potential benefits of the research and allowed to consent freely.

Ebonyi State is located in the Southeastern part of Nigeria. It shares boundaries with Benue State to the North, Enugu State to the Northeast, Abia State to Southeast and Cross River State to the East (Fig. 1). It is located between latitude 6o15’N and longitude 8o05’E. Ebonyi State is made up of 3 senatorial zones and 13 Local Government Areas (LGAs). The estimated total population in 2016 was 2,968,698 [8]. The climate of the area is tropical and the vegetation typical of the rain forest type. Average annual rainfall is 1,300 mm and average monthly temperature is of 30±5°C. There are 2 distinct seasons, the wet (between April and October) and the dry seasons (from November to March). Most rural communities in Ebonyi State is mainly flat tableland with the capacity to hold water after rainfall. These topographic features usually create breeding grounds for mosquito vectors. A number of streams and rivers traverse most rural communities in Ebonyi State and constitutes the major sources of water supply to the inhabitants of the communities. The occupation of most rural residents in Ebonyi State is primarily farming, growing major crops such as yam, cassava, and rice.

A total of 1,140 study participants aged from 1–100 years, comprised of males (n=540) and females (n=600) from 3 communities drawn from 3 LGAs in the 3 senatorial zones that make up Ebonyi State (1 LGA per senatorial zone) were screened for malaria parasite. Three hundred and eighty (380) participants were screened from each community. Participants consented to the study.

The sample size for this study was calculated using the formula below [9]

Where ME=margin of error, Z=z-score for confidence level, P=prior judgment or estimated prevalence, and n=sample size.

For this study, the confidence level was set at 95% and the z-score is 1.96: Margin of error=0.025 (2.5%). P (initial estimate of prevalence) was the prevalence of 24.5% in the rural community of Ezza North LGA of Ebonyi State [10] which puts “P” at 0.245.

The inclusion criteria for the malaria endemicity study were individuals who have resided in the study community for the past one month before the commencement of the study. They are not seriously sick at the time of the study.

The exclusion criteria for the malaria endemicity study were visitors to the community, infants below the age of 6 months (due to protection by passive immunity), people who have taken anti-malaria drug within the last month.

Malaria endemicity study was carried out in 3 communities, one each from Izzi, Onicha, and Ezza North LGAs of Ebonyi State. A total of 1,140 individuals (380 from each community) were examined for the presence of malaria parasite. All age groups ranging from 1–100 years comprised males and females were included. Sample collection was done on weekly basis. Rapid diagnostic test kits was used for the rapid diagnosis in the field while thick and thin smear slides for microscopy were prepared and transferred to the Medical Microbiology Laboratory of Ebonyi State University, Abakaliki where the slide were stained with 10% Giemsa and examined under a light microscope using x100 objective. All the samples collected each day were processed immediately after field collections. Slides that could not be examined the same day were continued the next day after proper staining. Prevalence rate was determined by calculating the percentage number of individuals infected with malaria parasite in the study population.

Rapid diagnosis was done using Rapid diagnostic test kit (RDT; SD Bioline malaria AG P.F/PAN kit, Standard Diagnostic. Seoul, Korea). The patient’s finger was cleaned and air dried. The cleaned finger was pricked with a sterile lancet and a drop of blood collected with a capillary device. The blood was dropped to the lower well (hole) on the RDT test kit. Two drops of buffer were added to the blood on the lower well. Fifteen minutes later, results were interpreted according to the manufacturer’s instruction and guidelines described by World Health Organization [11].

A drop of blood was stirred in a circular motion with a corner of slide. The film was allowed to dry without fixative, after which the smear was stained with 10% Giemsa for 20 min. The slides were washed by placing in a jar containing water for 3 min [12], and were later examined under a light microscope using x100 objective.

We smeared the blood with a swift and steady sweep along the surface of the slide. The film was air-dried and fixed with absolute methanol. The sample was stained with 10% Giemsa for 20 min [12] and were later examined under a light microscope using x100 objective.

Data was analyzed using SPSS version 20.0 (IBM, Chicago, Illinois, USA). Statistical difference in parasite prevalence among different age groups and sex was determined using Chi square.

Of the 1,140 individuals examined for malaria prevalence, 648 (56.8%) showed positive with RDT while 440 (38.6%) were re-confirmed positive with microscopy (Fig. 2). There was no significant difference in parasite prevalence between the 2 diagnostic methods (χ²=0.601, df=2, P=0.741 and χ²=0.718, df=2, P=0.698), respectively. The test performance of microscopy and RDT is presented in Fig. 3. The sensitivity and specificity values for microscopic examination were both 100%. Those of RDT were 95.5% and 75.9%, respectively. All cases recorded in this study were infection with Plasmodium falciparum.

The prevalence of malaria by age group with RDT examination was highest in 1–10 years (28.9%) and lowest in 91–100 years old (0.1%). Microscopic examination showed the highest prevalence (23.6%) among 1–10 years of age and lowest (0.1%) among age groups 51–60 years (Fig. 4). Statistically, there was no significant difference in the prevalence among the age groups with both diagnostic methods (χ²=16.371, df= 16, P=0.427 and χ²=11.380, df=12, P=0.497), respectively.

The prevalence of malaria by gender is shown in Fig. 5. RDT and microscopic examination revealed the higher prevalence (31.2% and 20.4%, respectively) in males than females (25.6% and 18.2%, respectively); however, no significance difference was observed in the prevalence between males and females (χ²=0.170, df=2, P=0.919 and χ²=1.865, df=2, P=0.394).

The highest prevalence of 19.5% with RDT was recorded in Onicha LGA while the lowest prevalence of 18.6% was shown in Izzi LGA. Microscopic examination showed the highest prevalence of 13.4% in Ezza North LGA and the lowest prevalence of 12.5% in Izzi LGA (Fig. 6). There were no significant differences in the prevalence of malaria among LGAs for both diagnostic methods (χ²=0.601, df=2, P=0.741 and χ²=0.718, df=2, P=0.698), respectively.

Table 1 shows a comparison of microscopic and RDT results. For microscopy, 440 samples tested were positive and 700 were negative. A total of 648 samples were positive and 492 were negative by RDT. Among the 440 positive cases diagnosed by microscopic examination, RDT failed to detect 20 cases. Out of the 700 negative cases by microscopic examination, 228 showed a positive reaction by RDT yielding 228 false positive results.