Study Setting and period
The data were collected during March-April, 2019 from HHs in five districts of Jimma zone namely; Limmu-Kossa, Botor-Tolay, Gera, Shebe-Sombo and Nono-Benja. Jimma zone has been one of malaria endemic settings in Ethiopia. The districts are in the range of 70-229 km from Jimma town (the capital of the zone). They also have high to medium risk of malaria. Moreover, 20 gandas (the lowest administrative of the government structure of the study setting) from each district were involved in the study. Across the districts, there are malaria programs rendering services and commodities for prevention and control (ITN, IRS and treatments).
The study used cross-sectional HH survey. In fact, the data was a portion of end line assessment of a school based social and behavior change communication (SBCC) interventions which was aimed to advance community malaria preventive practices. .
Population and Sample size
The survey was conducted among heads of the HHs. Given the study was merged with the SBCC project’s end line survey; we used the same sample that was used for evaluating the project. Initially, the project’s sample size was determined using two population proportion formula [(n= (Zα/2+Zβ)2 * (P1(1-P1)+P2(1-P2)) / (P1-P2)2]; where Zα/2 is the critical value of the normal distribution at α/2, at confidence level of 95% which gives a critical value of 1.96), Zβ is the critical value of the normal distribution at β (for a power of 80%, β is 0.2 and the critical value is 0.84) and to detect minimum difference (P1-P2) of 7.5% between the two proportions (baseline and end line) in ITN usage (P1=38.0%). This yielded 762 HHs.
We used multi-stage sampling. First, based on probability proportional to size of population, the sample size was allocated to each study district and Ganda. Twenty Gandas were randomly selected; 4 from each district. In each Ganda, three subdivisions (zoni) were represented in the study based on probability proportional to sizes of total HHs in selected Gandas. The HHs lists were obtained from family folders owned by respective Gandas. Finally, the HHs were selected using computer generated random numbers. The homes of the selected HHs were traced through local guiders.
Expected outcome variables
This study was mainly intended to examine access-use of ITN by target community based on HSI first, and then adapted with sleeping space. We hypothesized ownership-access-use of ITN would be more enhanced when ITN is accessed at actual sleeping space rather than mere availability in the HH. Obviously, ITN prevents malaria when HH members slept under it at actual sleeping space. Therefore, we intend to investigate how close the access-use of ITN based on HSI and SS.
Measurements and operational definitions
Ownership-access-use of ITN was measured by standard tools adopted mainly from a 2018 RBM guidelines for household survey indicators (HIS) for malaria control (18). The HSI include seven HH and population based proportions (P1-P7). The same proportions were estimated after adjustment to sleeping space- the alternative approach (SSP1-SSP7).
- HSI based estimates: household and population coverage and use of ITN
Indicator 1: Proportion of households (HHs) with at least one ITN (P1): measures HH ITN ownership i.e. the extent to which ITN programs have reached all households or, conversely, the not yet reached. It is calculated from the number of HHs surveyed with at least one ITN as a numerator, and the total number of HHs surveyed as a denominator.
Indicator 2: Proportion of HHs with at least one ITN for every two people (P2): measures the proportion of HHs that have a sufficient number of ITNs to cover all individuals who spent the previous night in surveyed HHs, assuming each ITN is shared by two people. It is calculated from the number of HHs with at least one ITN for every two people (HHs with people to ITN ratio of 2 or less) as a numerator, and the total number of HHs surveyed as a denominator. HHs with full coverage (enough nets) are indicated by value 1, the rest of HHs are assigned a value of 0. In connection with P1, P2 can be used to determine what proportion of HHs already reached with at least one ITN have a sufficient number of ITNs (saturation) to protect all members in the HH (this can be labeled as P5, in order to pick difference in denominator with P2) or conversely it describes the intra-HH ownership gap (1-P5) (i.e., HHs that own at least one ITN but do not have full coverage). If the difference between these indicators is substantial, programs need to assess whether current ITN distribution strategies should be revised to fill the saturation gap.
Indicator 3: Proportion of population with access to an ITN in their HH (P3): estimates the proportion of the HH population that could have slept under an ITN, assuming each ITN is used by two people. It is calculated from the total number of individuals who could sleep under an ITN if each ITN in the HH were used by two people (potential ITN users) as numerator, and the total number of individuals who spent the previous night in surveyed HHs as denominator. A “potential ITN users” is an intermediate variable calculated by multiplying the number of ITN in each HHs by two. In HHs having more than one ITN for every two people, the potential users will be equal to the number of people who slept in that HH last night. Therefore, after dividing the sum of all potential ITN users in the sample by the total number of individuals who spent the previous night in surveyed HHs, P3 gives any value between 0 and 1, indicating the magnitude of people who access ITN. If the difference between P3 and proportion of population sleeping under ITN the previous night (P4) is substantial, the program may need to focus on identifying the main drivers or barriers to ITN use to design an appropriate intervention for behavior change.
Indicator 4: Proportion of the population that slept under an ITN the previous night (P4): measures the level of ITN use among all individuals who spent the previous night in surveyed HHs, regardless of whether those individuals had access to an ITN in their HH. It is calculated from the number of individuals who slept under an ITN the previous night as numerator, and the total number of individuals who spent the previous night in surveyed HHs as denominator. It can be separately calculated for the children under five years old and pregnant women as the two most vulnerable population segments that need priority to sleep under ITN when the access is limited. This indicator can be compared with P3 to describe the magnitude of the behavioral gap in use of ITNs (i.e., the population that has access to an ITN but is not using it). This analysis is useful for informing ITN programs whether they need to focus on achieving higher ITN coverage, promoting ITN use, or both. This value can be labeled as P6.
- Adapted to sleeping space (SS/SS) based estimates of ITN coverage and use
In this case, sleeping space includes any room or space arranged for sleeping in the HH. The above HSI were all related with sleeping under ITN, indicating that where people sleep is worthy consideration.
Indicator 1: Proportion of HHs with ITN in at least any one of the sleeping spaces in the HHs (SSP1): measures sleeping space ITN ownership i.e. the extent to which ITN programs has reached SS in the HHs. It is calculated from the number of SS in HHs surveyed with ITN as a numerator, and the total number of SS in the HHs surveyed as a denominator.
Indicator 2: Proportion of HHs with ITN for every sleeping space in the HH (SSP2): measures the proportion of HHs having ITNs to cover all sleeping spaces in surveyed HHs, assuming each SS should have ITN. It is calculated from the number of HHs with ITN for every SS as a numerator, and the total number of SS in HHs surveyed as a denominator. This indicates the extent to which ITN can reach every SS of HHs in the community. If the denominator is limited to HHs with ITN for at least one SS, the value of saturation can be labeled SSP5, coverely the gap (1-SSP5)
Indicator 3: Proportion of population with access to an ITN in their SS in the HH (SSP3): estimates the proportion of the HH population that could have covered by ITN at SS. It is calculated from the total number of individuals who could sleep under an ITN given they are covered by ITN at SS as numerator, and the total number of individuals who spent the previous night in surveyed HHs as denominator. It is interpreted as proportion of people covered by ITN at their respective SS in that HH.
Indicator 4: Proportion of the population that slept under an ITN the previous night (SSP4=P4). It is calculated from the number of individuals who slept under an ITN the previous night as numerator, and the total number of individuals who spent the previous night in surveyed HHs as denominator. If P4 is limited to denominator of people with access to ITN at where they sleep, it is labeled SSP6. This can pick the seasonality or occasions when people covered by ITN at where they sleep also use it.
Data collection procedures
The data were collected through face to face interviewer administered method. The interview was conducted by trained experienced interviewers under supervision in Afaan Oromo language. Three days training about the purpose of the study, instruments and data collection procedures was given. The data were cleaned, checked for consistency on daily basis. The research team supervised overall data collection process.
The data were analyzed by using SPSS version 20.0. We referred to operational definitions set by 2018 RBM’s HSI and adapted SS indicators to determine ownership-access-use of ITN. We used proportions with 95% confidence interval to describe the key indicators. Moreover, we determined discrepancies within and between, compared the closeness of the estimates, interpreted the implications and finally identified relevance of complementation of the two HIS and adapted SS indicators, particularly for ownership and access measures. Bivariate analysis (Chi-square) was performed to determine patterns of access-use of ITN along social-spatial variables. Odds ratio was executed between ITN use and sufficiency and access based on the two approaches. Moreover, we recommended malaria prevention and control programs an operational diagrammatic solution to improve access-use of ITN.
Ethical approval and considerations
The study was approved by Jimma University, Institute of health institutional review board for Institute of Health. Official permissions to undertake the study were obtained from concerned bodies. Respondents were given detailed information about the purpose of the study. Informed written consent was obtained from all study participants.