| Literature DB >> 29764426 |
Adedayo O Oduola1, Abiodun Obembe2, Olukayode J Adelaja3, Adeniyi K Adeneye4, Joel Akilah5, Taiwo S Awolola4.
Abstract
BACKGROUND: Despite the availability of effective malaria vector control intervention tools, implementation of control programmes in Nigeria is challenged by inadequate entomological surveillance data. This study was designed to assess and build the existing capacity for malaria vector surveillance, control and research (MVSC&R) in Nigerian institutions.Entities:
Keywords: Capacity building intervention; Malaria; Nigerian institutions; Personnel; Research; Surveillance; Training; Vector control
Mesh:
Year: 2018 PMID: 29764426 PMCID: PMC5952629 DOI: 10.1186/s12936-018-2344-z
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Fig. 1Number of applications received from each of the six geo-political zones in Nigeria
Fig. 2Distribution of participants for the CB training workshop across the six geopolitical zones in Nigeria
Gender, geopolitical zone and institution spread of applicants selected for the capacity building training workshop
| S/N | Region | Address/institution | Sex |
|---|---|---|---|
| 1 | North Central | Department of Biological Sciences, Federal University of Technology, Minna | M |
| 2 | North Central | Department of Parasitology and Entomology, Faculty of Veterinary Medicine, University of Abuja, Abuja-FCT, Nigeria | M |
| 3 | North Central | Department of Biological Sciences, Kogi state University, Anyigba | F |
| 4 | North Central | Department of Biological Sciences, University of Agriculture, Makurdi, Benue State | M |
| 5 | North West | Department of Biological Sciences, Kaduna State University | M |
| 6 | North West | Department of Biological Sciences, Sule Lamido University, Kafin Hausa, Jigawa State | M |
| 7 | North West | Department of Biological Sciences, Federal University, Dutse, Jigawa State | M |
| 8 | North East | Department of Biological Sciences, Gombe State University | M |
| 9 | North East | School of Science Education, Federal College of Education (TECH), Potiskum, Yobe | M |
| 10 | North East | Department of Biological Sciences, University of Maiduguri | M |
| 11 | North East | Department of Biological Sciences, Gombe State University | M |
| 12 | South West | Department of Pure and Applied Zoology, Federal University of Agriculture, Abeokuta | F |
| 13 | South West | Federal University, Oye-ekiti | F |
| 14 | South West | Olabisi Onabanjo University, Ago Iwoye, Ogun state | M |
| 15 | South West | Department of Pure and Applied Zoology, Federal University of Agriculture, Abeokuta | M |
| 16 | South West | Department of Zoology, Ekiti State University, Ado-Ekiti | M |
| 17 | South South | Calabar Institute of Tropical Disease, Research and Prevention, University of Calabar Teaching Hospital | M |
| 18 | South South | Isaac Jasper Boro College of Education, Sagbama, Yenagoa, Bayelsa | M |
| 19 | South East | Department of Zoology and Environmental Biology, University of Agriculture Umudike, Abia | M |
| 20 | South East | Applied Biology Unit, Department of Biological Sciences, Ebonyi State University | F |
| 21 | South East | Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka, Anambra | F |
| 22 | South East | Biology/Microbiology Department, Abia State Polytechnic, Abia | F |
| 23 | South East | National Arbovirus and Vectors Research Center, Enugu | M |
Socio-demographic data of participants at the malaria capacity building workshop
| Parameters | Distribution of participants |
|---|---|
| Frequency (%) | |
| Total no. of participants | 23 |
| Geopolitical zones | |
| South-West | 5 (21.7) |
| South-East | 4 (17.4) |
| South-South | 2 (8.7) |
| North-Central | 5 (21.7) |
| North-West | 3 (13.0) |
| North-East | 4 (17.4) |
| Ethnicity | |
| Igbo | 6 (26.1) |
| Hausa | 3 (13.0) |
| Yoruba | 6 (26.1) |
| Minority | 8 (34.8) |
| Gender | |
| Male | 17 (73.9) |
| Female | 6 (26.1) |
| Age group (years) | |
| 26–35 | 13 (56.5) |
| 36–45 | 10 (43.5) |
| Designation (career status) | |
| Early career | 13 (56.5) |
| Middle career | 9 (39.1) |
| Senior career | 1 (4.4) |
Discipline and institution of faculties selected for the CB workshop
| S/N | Institution | Discipline |
|---|---|---|
| 1 | University of Ilorin Teaching Hospital, Ilorin | Malariologist |
| 2 | University of Ilorin | Insect Ecologist |
| 3 | University of Ilorin | Parasitologist |
| 4 | United States Presidential Malaria Initiative. African Indoor Residual Spray | Technical Manager (Indoor Residual Spraying) |
| 5 | Integrated Vector Management National Malaria Elimination Programme, Abuja | IVM, Federal Ministry of Health, Policy |
| 6 | World Health Organization | National Programme Officer (Malaria) |
| 7 | Nigerian Institute of Medical Research, Lagos | Malaria Entomologist |
| 8 | Nigerian Institute of Medical Research, Lagos | Medical Sociologist |
| 9 | University of Ilorin | Molecular Biologist |
| 10 | Federal University Oye, Ekiti State | Pesticide Scientist |
| 11 | Lead City University, Ibadan | Entomologist |
| 12 | University of Ilorin | Entomologist/Field Officer |
| 13 | Harvestfield Industries Ltd | Indoor Residual Spray Specialist |
| 14 | Kwara State University | Field Entomologist |
| 15 | Osun State Malaria Elimination Programme | Public Health Specialist/Training Manager |
| 16 | University of Ilorin | Social Network Manager |
| 17 | Nigerian Institute of Medical Research, Yaba, Lagos | Biochemist |
Distribution of scores of participants during the pre-and post-test assessments of knowledge on field techniques
| Pre-test number of participants | Participants score range (%) | Post-test number of participants | |
|---|---|---|---|
| 8 | 10–20 | 0 | |
| 5 | 21–30 | 0 | |
| 7 | 31–40 | 0 | |
| 3 | 41–50 | 0 | |
| 0 | 50–60 | 5 | |
| 0 | 61–70 | 7 | |
| 0 | > 71 | 10 | |
| Total | 23 | 22 |
Fig. 3Minimum, percentiles and maximum scores of participants before and after training in field techniques
Distribution of scores of participants during the pre-and post-test assessments of knowledge on laboratory techniques
| Number of participants (pre-test) | Participants score range (%) | Number of participants (post-test) | |
|---|---|---|---|
| 1 | 20–29 | 0 | |
| 7 | 30–39 | 0 | |
| 4 | 40–49 | 0 | |
| 0 | 50–59 | 1 | |
| 0 | 60–69 | 1 | |
| 0 | 70–79 | 5 | |
| 0 | > 80 | 5 | |
| Total | 12 | 12 |
Fig. 4Minimum, percentiles and max scores of participants before and after training in laboratory techniques
Evaluation of participants’ previous access to field tools and techniques in malaria vector surveillance control and research
| Parameters | Participants experience with respect to geopolitical zones n (%) | p value | ||||||
|---|---|---|---|---|---|---|---|---|
| North-Central | North-East | North-West | South-West | South-East | South-South | Total | ||
| Previous involvement with exit light traps | a | |||||||
| Yes | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| No | 5 (22.7) | 4 (18.2) | 3 (13.6) | 4 (18.2) | 4 (18.2) | 2 (9.1) | 22 (100) | |
| Previous involvement with CDC light traps | 0.414 | |||||||
| Yes | 0 | 1 (33.3) | 0 | 0 | 1 (33.3) | 1 (33.3) | 3 (13.6) | |
| No | 5 (26.3) | 3 (15.8) | 3 (15.8) | 4 (21.1) | 3 (15.8) | 1 (5.3) | 19 (86.3) | |
| Previous involvement with questionnaire | 0.841 | |||||||
| Yes | 4 (22.2) | 3 (16.7) | 2 (11.1) | 4 (22.2) | 3 (16.7) | 2 (11.1) | 18 (81.8) | |
| No | 1 (25.0) | 1 (25.0) | 1 (25.0) | 0 | 1 (25.0) | 0 | 4 (18.2) | |
| Previous involvement with PSC | 0.044 | |||||||
| Yes | 1 (14.3) | 3 (42.9) | 0 | 0 | 1 (14.3) | 2 (28.6) | 7 (31.8) | |
| No | 4 (26.7) | 1 (6.7) | 3 (20.0) | 4 (26.7) | 3 (20.0) | 0 | 15 (68.2) | |
| Previous involvement with mosquito identification | 0.220 | |||||||
| Yes | 1 (10.0) | 3 (30.0) | 2 (20.0) | 1 (10.0) | 1 (10.0) | 2 (20.0) | 10 (45.5) | |
| No | 4 (33.3) | 1 (8.3) | 1 (8.3) | 3 (25.0) | 3 (25.0) | 0 | 12 (54.5) | |
| Previous involvement with mosquito identification keys | 0.642 | |||||||
| Yes | 2 (16.7) | 3 (25.0) | 2 (16.7) | 1 (8.3) | 3 (25.0) | 1 (8.3) | 12 (54.5) | |
| No | 3 (30.0) | 1 (10.0) | 1 (10.0) | 3 (30.0) | 1 (10.0) | 1 (10.0) | 10 (45.5) | |
| Previous involvement with IRS | 0.078 | |||||||
| Yes | 0 | 2 (100) | 0 | 0 | 0 | 0 | 2 (9.1) | |
| No | 5 (25.0) | 2 (10.0) | 3 (15.0) | 4 (20.0) | 4 (20.0) | 2 (10.0) | 20 (90.1) | |
| Previous involvement with susceptibility bioassays | 0.027 | |||||||
| Yes | 0 | 4 (50.0) | 1 (12.5) | 0 | 2 (25.0) | 1 (12.5) | 8 (36.4) | |
| No | 5 (35.7) | 0 | 2 (14.3) | 4 (28.6) | 2 (14.3) | 1 (7.1) | 14 (63.6) | |
| Previous involvement with larval bioassays | 0.878 | |||||||
| Yes | 1 (20.0) | 1 (20.0) | 0 | 1 (20.0) | 1 (20.0) | 1 (20.0) | 5 (22.7) | |
| No | 4 (23.5) | 3 (17.6) | 3 (17.6) | 3 (17.6) | 3 (17.6) | 1 (5.9) | 17 (77.3) | |
| Previous involvement with community project | 0.492 | |||||||
| Yes | 3 (16.7) | 3 (16.7) | 2 (11.1) | 4 (22.2) | 4 (22.2) | 2 (11.1) | 18 (81.8) | |
| No | 2 (50.0) | 1 (25.0) | 1 (25.0) | 0 | 0 | 0 | 4 (18.2) | |
a No measure of association because no values were recorded for ‘yes’ variable
Assessment of participants’ access to laboratory tools in malaria vector surveillance and control research
| Parameters | N (%) |
|---|---|
| Have you ever carried out a polymerase chain reaction assay before? | 12 (100) |
| Have you ever been involved in DNA extraction before? | 11 (91.6) |
| Have you designed or used a primer before? | 12 (100) |
| Have you ever prepared an agarose gel before? | 12 (66.7) |
| Have you ever used a ultra violet photo-documentation system before? | 12 (66.7) |
| Have you ever determined sporozoite infection rate before? | 11 (91.7) |
| Have you ever used a spectrophotometer/microplate reader before? | 11 (91.6) |
| Do you have an insectary in your institution? | 10 (83.3) |
N number of participants with negative response
Fig. 5Compliance of participants to mentoring checklist of activities