A total of 26 articles were identified that met inclusion criteria. These studies provided information on two key areas of interest: when (time of night) and where (indoors versus outdoors) people are exposed to malaria vectors and characterization of night time activities occurring during hours when malaria vectors are active.
Human exposure to malaria vectors
Ten studies integrated human behavioural and entomological data to provide a quantitative estimate of human-vector interaction occurring indoors and outdoors (Table
2).
Table 2
Studies quantifying human-vector interaction
Killeen et al. (2006) [ 20] | Tanzania | Survey | Usual bed time and wake-up time | Indoor and outdoor HLC, 6:00 p.m.–6:00 a.m. | Mosquito collections: 1997 and 2004 Survey: 2002–2004 | Indoor exposure for non-user: 90% Indoor exposure during sleeping hours (9:00 p.m.–5:00 a.m.): 80% Protective efficacy of an ITN: 70% |
Geissbuhler et al. (2007) [ 21] | Tanzania | Survey and direct observation | Survey: Dinner location, location after dinner, usual bed time and wake-up time, use of prevention measures Direct observation: People outdoors for each hour of the night | Indoor and outdoor HLC, 6:00 p.m.–7:00 a.m. | Mosquito collections: April-June 2006 Survey: Carried out in same households; exact timing not specified | Indoor exposure for non-user (An. gambiae s.l.): 79% Indoor exposure during sleeping hours for non-user (An. gambiae s.l.): 74% Protective efficacy of an ITN (An. gambiae s.s.): 59% Protective efficacy of an ITN (An. arabiensis): 38% |
Russell et al. (2011) [ 22] | Tanzania | Survey | Usual bed time Usual wake-up time | Indoor and outdoor HLC, 7:00 p.m.–7:00 a.m. | Mosquito collections: 1997, 2004, and 2009 Survey: 2002–2004 | Indoor exposure for non-user (1997 An. gambiae s.l.): 92% Indoor exposure for non-user (2004 An. gambiae s.l.): 99% Indoor exposure for non-user: (2009 An. gambiae s.l.): 79% Indoor exposure for non-user (1997 An. funestus): 93% Indoor exposure for non-user (2004 An. funestus): 73% Indoor exposure for non-user (2009 An. funestus): 45% |
Seyoum et al. (2012) [ 23] | Zambia | Survey | Usual time indoors for the night, bed time, wake-up time, time to leave home in the morning, use of ITNs | Indoor and outdoor HLC, 7:00 p.m.–7:00 a.m. | Mosquito collections: September–October 2009, February–March 2010 Survey: April 2010 | Indoor exposure for non-user (An. funestus): 98% Indoor exposure for non-user (An. quadriannulatus): 97% Indoor exposure for ITN-user (An. funestus): 57% Indoor exposure for ITN-user (An. quadriannulatus): 58% |
| Burkina Faso Kenya Tanzania Zambia | Burkina Faso and Tanzania: Direct observation by field worker 6:00 p.m. until all household members went to sleep and 4 a.m.–6 a.m. Kenya and Zambia: Malaria indicator survey | Observation: Household members awake, by hour Survey: To the nearest hour, time that each household member went indoors, to bed, woke up, and left the home | Indoor and outdoor HLC, start time ranged from 6:00 p.m. to 8:00 p.m. and end time ranged from 6:00 a.m. to 7:00 a.m. across sites | Tanzania and Burkina: 2001 and 2004 Kenya and Zambia: 2009 and 2010 Exact timing of entomological and human behavioural data collection was not provided | Indoor exposure for non-user (An. gambiae s.l.): ranged from 87 to 97% across sites Indoor exposure for non-user (An. funestus s.l.): ranged from 62 to 97% |
| Kenya | Survey | ITN use, usual time indoors for the night, bed time, wake-up time, time to leave home in the morning | Indoor and outdoor HLC, 5:00 p.m.–7:00 a.m. | Mosquito collections: June–July 2011 Survey: July–August 2011 Data compared to data from previous study carried out in 1989–1990 | Indoor exposure for non-user: > 90% in all years Indoor exposure for non-user during sleeping hours: ≥ 90% for all species except for An. arabiensis (97% in 1989/1990; 80% in 2009; 84% in 2011) Indoor exposure for ITN-user during sleeping hours: (64–77% in 1989–1990; 20–52% in 2009 and 2011) |
Moiroux et al. (2014) [ 26] | Benin | Survey | Time each household member entered and exited the house the night before the survey and entered and exited the sleeping space | Indoor and outdoor HLC, 11:00 p.m.–9:00 a.m. | Mosquito collections: April 2011 Survey: March 2013 | Indoor exposure for non-user: 86% and 94% in the two study sites Protective efficacy of an ITN: 80% and 87% Indoor exposure for ITN-user: 55% and 31% |
| Kenya | Survey completed by head of household on behalf of household members, using digital watch | Time household members entered and exited the house, time to sleep, and use of ITNs | CDC light-traps set next to occupied ITNs, emptied hourly Indoor traps 5:30 p.m.–5:30 a.m.; outdoor traps 5:30 p.m.–10:30 p.m. only | Mosquito collections: June 2011–May 2012 Survey: June 2011–May 2012 | Indoor exposure for non-user: 95% (31% before bed and 64% while asleep) Protective efficacy of an ITN:51% |
Bradley et al. (2015) [ 28] | Equatorial Guinea-Bioko Island | Annual malaria indicator survey | Time household members entered the house the night before, any other time spent outside the house between 7:00 p.m. and 6:00 a.m., bed time | Indoor and outdoor HLC, 7:00 p.m.–6:00 a.m. | Mosquito collections: January-October 2009-2013 Survey: 2013 | Indoor exposure for non-user: 80% |
| Kenya | Survey administered to head of household | Time each household member went to sleep and woke up | HLC and CDC light traps; 6:00 am–6:00 pm | Mosquito collections: July and August 2016 Survey: September and October 2016 | Indoor exposure for non-user (children < 5): 90% |
Studies that integrated human and vector data used estimates of indoor and outdoor vector biting as well as the distribution of people indoors and outdoors for each hour of the night to produce a weighted estimate of exposure occurring indoors and outdoors. This analytical approach was used to quantify human-vector interaction by Killeen et al. in rural Tanzania [
20]. In this study, human landing catches were used to assess nightly mosquito biting behaviour before and after widespread coverage of ITNs. The proportion of time people spent indoors and outdoors was estimated based on self-reported survey questions on when household members went to bed and woke up in the morning. These data were combined with hourly indoor and outdoor biting rates to calculate the proportion of bites that occur indoors for unprotected individuals, the proportion of bites that occur during sleeping hours, and the “true protective efficacy of an ITN”, defined as the overall reduction in nightly biting rate for an ITN user compared to a non-user.
Variations of this approach to measuring human-vector interaction were found in nine subsequent publications [
21‐
29]. Mosquito biting behaviour was measured in the majority of studies using human landing catches (HLC) indoors and outdoors on an hourly basis. Cooke et al. used CDC light traps and human baited ITNs [
27]. All of the studies focused mosquito collections on the peri-domestic setting, which included inside of dwellings and in the outdoor space directly outside of the dwelling [
30]. Mosquito collections were generally carried out indoors and outdoors, from dusk until dawn, with some variation in start and end times across study sites.
The human behavioural variables of interest and approach used to calculate indoor and outdoor components of human-vector interaction were similar across studies. Like the study by Killeen et al., these studies included estimates of time spent indoors and outdoors throughout vector biting hours, however in some cases they used different methods to derive these estimates. For example, Cooke et al. provided digital watches to heads of household and had them fill out surveys on household members’ night time behaviour [
27]. Geissbuhler et al. used self-reported survey data, validated by a smaller number of evening observations [
21]. Huho et al. looked at human-vector interaction across countries, using different methods for measuring human behaviour in different locations [
24]. This included direct observation of night time behaviour from 6:00 p.m. to bedtime and 4:00 a.m. to 6:00 a.m. in selected sites in Tanzania and Burkina Faso, and self-reported survey data from malaria indicator surveys in Zambia and Kenya. The two methods were not compared to one another. Bradley et al. also used data from questions included in a malaria indicator survey [
28]. Other studies used self-reported survey data to gather similar information to Killeen et al. The exact list and phraseology of the questions was not included in all publications, but differences in content were identified. Some studies only asked about the time participants went to bed and woke up, while others included additional questions on time participants went inside the house and time they went outside in the morning to more closely approximate when people were outdoors, indoors and awake, and indoors and asleep.
The most common human-vector indicators presented in the studies reviewed included proportion of exposure to malaria vectors occurring indoors for an unprotected individual, exposure to malaria vectors occurring indoors during sleeping hours for an unprotected individual, exposure occurring indoors for an ITN user, and protective efficacy of an ITN. However, these indicators were not uniformly calculated and were not included across all studies integrating human and vector data.
Across settings, a majority of human exposure to malaria vectors for non-users of ITNs was found indoors, largely during sleeping hours. However, variation was observed across settings. In Western Kenya, Cooke et al. found that without the protection of an ITN over 90% of exposure occurred indoors, similar to estimates from Killeen et al. in the Kilombero Valley of Tanzania, Seyoum et al. in South-East Zambia, Bayoh et al. in western Kenya, Moiroux et al. in south Benin, and Huho et al. in six sites in rural Burkina Faso, Kenya, Zambia, and Tanzania [
20,
23‐
27]. However, Cooke et al. found that use of an ITN could prevent only about half of exposure to malaria vectors despite predominantly endophagic primary vectors, likely due to high levels of indoor exposure before sleeping hours [
27]. Kamau et al. estimated the fraction of exposure occurring indoors and outdoors for children under five. Overall, the study estimated that 10% of exposure is happening outdoors, primarily during early evening hours between 6:00 p.m. and 9:00 p.m. [
29].
Results suggest shifts in both time and place (indoor/outdoor) of exposure across time. Russell et al. found significant changes in indoor human exposure to malaria vectors for both
An. gambiae s.l. and
An. funestus as ITN use increased [
22]. In 1997, over 90% of exposure occurred indoors for both vector species; by 2009 when ITN access and use had increased, indoor exposure dropped to 79% for
An. gambiae s.l. and. 45% for
An. funestus and a higher proportion of exposure outdoors during early evening hours was observed. The protective efficacy of an ITN varied from approximately 50% to over 80% in studies that reported on it, with even lower protective efficacy (38%) reported for specific vector species, namely
An. arabiensis [
20,
21,
26,
27].
Association between night time location and malaria risk
Seven studies were identified that linked night time location with malaria risk. Four of the six studies specifically looked at whether time spent outdoors at night was associated with an increased risk of malaria infection. A case control study in South-West Kenya by Githinji et al. assessed micro-ecological and human behavioural factors associated with an increased risk of malaria infection. Human behaviour was assessed through a standardized survey [
31]. No detail on the content of the human behavioural survey questions was included in the methods section. Results showed participants who spent time outside at night were more likely to be infected with malaria. Spending time outside at night was binary and did not specify length of time or time of the night. The discussion section described ‘
experiences gathered during data collection period’ that showed community ceremonies such as funerals were commonly carried out at night, leading to an increased exposure to the risk of mosquito bites. However, no description was provided in the study methods about how night time activities were recorded nor was this information included in the results section.
In two studies, Bradley et al. investigated the association between time spent outdoors and malaria infection on Bioko Island, Equatorial Guinea. In a 2012 publication, Bradley analysed data from an annual malaria indicator survey, which includes a question asking whether a child spent time outside between 10 p.m. and 6 a.m. [
32]. Children aged two to fourteen were tested for
Plasmodium falciparum using rapid diagnostic tests (RDT). Only 4% of children were reported to spend time outside during this time and no significant difference in prevalence was observed for children who spent time outside verses those who did not. In a 2015 publication, Bradley et al. conducted a survey to measure the association between time spent outdoors and malaria infection as measured by RDT, in addition to measuring exposure to malaria vectors [
28]. Malaria infection was not significantly higher in individuals who reported spending time outside between 7:00 p.m. and 6:00 a.m. the previous night compared to those who did not, in both adults and children. Malaria infection in neither adults nor in children was associated with exposure to outdoor bites, even after adjusting for confounders.
Mwesigwa et al. assessed incidence of
P. falciparum infection using a cohort study in The Gambia [
33]. The study included a household survey that asked about outdoor sleeping among household members. Outdoor sleeping varied by season and was associated with a significantly higher risk of malaria infection.
Hetzel et al. carried out a longitudinal study looking at time spent at
shamba (farm houses) and incidence of fever in rural Tanzania [
34]. The study included a survey to record where household members spent time during the day and night and use of ITNs as well as a treatment-seeking questionnaire recording fever episodes and treatment-seeking behaviour. During weeding and harvesting seasons a large proportion of household members spent days and nights at the farm houses. Fever incidence rates were lower in the
shamba compared to the village, and 97% of participants reported using a mosquito net the night before. The discussion noted that since
shamba houses are spread out there is little opportunity for socializing in the evening and, therefore, household members were likely to go to bed early; however, information on night time social activities and average bed times were not reflected in the study methods or results.
Using global positioning system (GPS) data loggers, Searle et al. assessed seasonal movement patterns in rural Southern Zambia [
35]. As part of the study, the team assessed time spent away from the household compound during peak biting hours, defined as 7:00 p.m. to 6:00 a.m. for the primary local vector,
An. arabiensis. On average, participants spent 5.6% of time away from the household compound during peak vector biting hours. Time spent in high or low risk areas, identified by a malaria risk map, depended on the level of risk for the area in which a participant’s compound was located. Participants largely spent time in and close to their household compound, with less frequent longer distance movements. While the study assessed time away from the household compound during peak biting hours, the spatial resolution of the loggers was not sufficient to distinguish time spent indoors and outdoors specifically.
Ototo et al. included the percentage of the population outdoors during times of the night when the highest densities of blood fed vectors were collected in a study in Kenya [
36]. Approximately half of the study population was outdoors in the evening between 6:00 p.m. and 8:00 p.m. and in the morning between 6:00 a.m. and 8:00 a.m. In the highland sites, participants reporting going outdoors earlier in the morning compared to the lowland sites, between 4:00 a.m. and 6:00 a.m., largely due to agricultural activities. The results show that no one slept outdoors, even in the hot months. While presented together, the data were not integrated to provide an estimate of exposure to malaria vectors.
Characterization of night time activities
A total of 10 studies included some description of night time activities occurring during times when local malaria vectors are active (Table
3). These studies identified activities taking place in the peri-domestic setting (inside and directly outside of the home), as well as away from home, throughout the night. This included routine household chores and entertainment occurring in the evening hours before bed, routine livelihood activities that lasted throughout the night such as security and fishing, and large-scale socio-cultural events, such as weddings and funerals which lasted throughout the night. Circumstances that could temporarily disrupt usual sleeping patterns were also described including travel, illness, and house guests, as well as seasonal changes to sleeping patterns associated with farming practices and outdoor sleeping.
Table 3
Studies including description of night time human activities
| Kenya | Early morning (4:00 a.m.–6:00 a.m.) observation of ITN use Survey question on barriers to ITN use for children under 5 | Funeral ceremonies Disruption of sleeping patterns due to visitors | Large-scale socio-cultural events travel/visitors |
| Tanzania | In-depth interviews Focus group discussions Participatory methods | Spending night at farming plot Outdoor sleeping Socio-cultural events e.g. funerals Household chores (women) Drinking, watching television, and socializing (men) | Livelihood activities Large-scale socio-cultural events Routine household activities Entertainment |
| Ghana | Survey | Outdoor sleeping | Outdoor sleeping |
Monroe et al. (2014) [ 39] | Uganda | In-depth interviews Focus group discussions | Funerals, weddings, religious events, parties Socializing, visiting bars Overnight visits with friends/family Occupations such as police and fishing Outdoor sleeping Domestic disputes, insurgency, illness | Large-scale socio-cultural events Entertainment Travel/visitors Livelihood activities Outdoor sleeping Times of difficulty |
Dlamini et al. (2015) [ 40] | Swaziland | In-depth interviews Focus group discussion Direct observation from morning to late evening | Soccer playing and socializing (adolescent boys) Drinking at local bars (men) Preparing meals and fetching water (women and adolescent girls) | Entertainment Routine household activities |
Monroe et al. (2015) [ 41] | Ghana | Direct observation (6:00 p.m.–6:00 a.m.) In-depth interviews | Household chores Socializing Weddings, funerals Outdoor sleeping | Routine household chores Entertainment Large-scale socio-cultural events Outdoor sleeping |
| Tanzania | Direct observation (6:00 p.m.–7:00 a.m.) In-depth interviews Focus group discussions | Farming practices Relaxing and storytelling, playing Cooking, eating, fetching water and firewood | Livelihood activities Routine household activities |
| Tanzania | In-depth interviews Focus group discussions | Cooking, eating, household chores Socializing, drinking at bars | Routine household activities Entertainment |
Masalu et al. (2017) [ 44] | Tanzania | Focus group discussions | Farming, night guard, sex work Funerals, parties, and gatherings | Livelihood activities Large-scale socio-cultural events |
Makungu et al. (2017) [ 45] | Tanzania | In-depth interviews Focus group discussions Photovoice methods | Household chores Watching television, drinking at bars Fishing, street vending Funeral ceremonies | Routine household activities Entertainment Livelihood activities Large-scale socio-cultural events |
Methods used to document and characterize human behaviour included in-depth interviews, focus group discussions, participatory methods (e.g. mapping, diagramming, and photovoice recordings), direct observation of night time events, and questionnaires. These studies often looked at specific night time activities, as well as the impact of these activities on use of malaria prevention tools.
The level of detail provided on night time activities and sleeping patterns varied widely across publications. In some studies, night time human behaviour was the primary area of focus. For example, Dunn et al. explored shifting household sleeping patterns in response to livelihood practices and socio-cultural events, and how these could impact malaria exposure and prevention practices in rural Tanzania [
38]. The study documented changes in daily and seasonal sleeping patterns associated with farming practices that could impact human-vector interaction either through differences in time spent indoors/outdoors or differences in use of ITNs. The study also identified risk behaviours during socio-cultural events, such as funeral ceremonies, that could impact time spent outdoors and use of ITNs.
In a study by Monroe et al. in Uganda, spending time away from home at night emerged as an important theme for understanding potential malaria exposure and prevention practices [
39]. Social events, livelihood activities, and "times of difficulty” were identified as circumstances in which people spend part or all of the night away from home. Social events included funerals, weddings, religious ceremonies, spending time at bars and discos, and visiting friends and family. Livelihood activities included professions such as police, security guards, soldiers, fishermen, and brick-makers who might stay outside all night as part of their job. Times of difficulty at the family and community level included domestic violence or disputes, and security issues. Social barriers inhibited net use away from home as people feared being perceived as rude or as showing off if they brought their nets to large or small-scale social events. Not having a place to hang the net, or not having enough nets at home to take one when staying away, were also barriers.
A study by Monroe et al. in northern Ghana included both in-depth characterization of night time activities and assessment of potential human-vector interaction. In addition to in-depth interviews with community members and health workers, and semi-structured observations of night time activities and sleeping patterns throughout the night, the study team observed when people were indoors or outdoors, under a net, and sleeping for each household member at half-hourly intervals throughout the night. Entomology data were not collected as part of the study, however biting times from entomological monitoring in nearby sites was discussed in relation to human activities and sleeping patterns throughout the night [
41]. This study identified a range of routine household chores, social activities, and large-scale events that may impact exposure to malaria vectors and use of prevention tools. Large-scale socio-cultural events and outdoor sleeping were the most common reasons for people to be outside during peak vector biting hours in the middle of the night.
In other studies, night time activities were included to a smaller extent as part of a larger research study. Alaii et al. monitored ITN use through early morning observations following net distribution. A household survey included a question on reasons why children under five might not use a net. Among those that provided reasons, social reasons accounted for a third of responses and included disruption of sleeping arrangements, funerals, visitors, and illness. Entomological indices were calculated in control villages but were not integrated with the human behavioural data [
37].
Masalu et al. conducted a study to test transfluthrin-treated decorative baskets and wall decorations at bars and included a small number of focus groups to assess acceptability of the products [
44]. Focus group discussion respondents noted common night time activities, including farming, night guarding, sex work, funerals, parties, and other gatherings as activities that could increase risk of exposure to malaria. Mosquito collections were carried out in bars but were not linked with human behavioural data.
Dlamini et al. used a combination of semi-structured interviews, focus group discussions, and observations to identify behaviours that might impact malaria control interventions. Group socialization outside late into the evening at soccer games, friends’ houses, or drinking establishments was found to be the primary behaviour keeping people from using ITNs during vector biting hours. These activities were most common among young men. Preparing meals and fetching water were identified as common activities for women and girls [
40].
A study by Tuno et al. in Ghana included a survey to determine the frequency of outdoor sleeping in study sites as well as where and when participants slept outdoors. The findings from this component of the study were presented separately from the entomological component. A significant proportion of men (37% and 82%) and women (16% and 56%) reported sleeping outdoors for a portion of the night in the two sites.
Swai et al. looked at biting risk associated with migratory farming practices. In addition to looking at mosquito biting behaviour, the frequency of night time human activities (cooking, eating, washing dishes, fetching water and firewood, and storytelling) was recorded through direct observation. These activities were frequently observed during the times when the highest biting rates were recorded for local vectors, between 6:00 p.m. and 11:00 p.m. While human and vector data were collected and analysed together to describe where humans may be at risk, the data was not integrated to provide a quantitative estimate of indoor and outdoor exposure based on the distribution of humans and vectors throughout the night [
42].
As part of a qualitative study, Moshi et al. used in-depth interviews and focus group discussions to better understand community knowledge of malaria transmission. The study described time spent outdoors, primarily during the early evening hours. During this time household chores, such as cooking, and socializing were common. Sitting outdoors at bars was described as a common activity for males [
43]. Likewise, Makungu et al. used focus group discussions, in-depth interviews, and photovoice methods to capture perceptions and practices around mosquito control. Participants described gaps in protection when they were outdoors, particularly during livelihood and leisure activities. Examples of activities that kept people outside at night included fishing, street vending, watching television, drinking at bars, and attending funeral ceremonies [
45].
While some differences were noted across settings, activity categories were largely consistent across studies, including activity timing, duration, frequency, and location (Table
4). Within the peri-domestic space, household members engaged in chores, socializing, and relaxing on a nightly basis. Likewise, entertainment activities and small business activities occurred within the community, away from the peri-domestic setting, on a nightly basis, most commonly for adolescent and adult males. Livelihood activities occurred nightly or seasonally and impacted a smaller segment of the study populations. Large-scale social events such as weddings, funerals, and religious events were common across settings and often involved males and females of all ages.
Table 4
Night time Activity Categories
Routine household activities | Common across settings; involves a large segment of the population; household chores most common among adolescent and adult females | Daily | Evening and early morning | Indoors and outdoors within the peri-domestic space |
Routine livelihood activities e.g. security | Common across settings; most common among adult males | Daily | All-night | Outdoors within the community or beyond |
Seasonal livelihood activities e.g. farming | Varies by setting | Seasonal | Early morning and evening or in some cases staying at farm plots for days or weeks | Away from home |
Large-scale socio-cultural events | Common across settings and involves a large segment of the population | Variable | All-night | Outdoors within the community or beyond |
Entertainment e.g. bars, watching television | Common across settings; most common among adolescent and adult males | Daily | Evening and late night | Outdoors within the community |
Travel/visiting | Varies by setting | Variable | All-night | Outside of the community; likely indoors |
Outdoor sleeping | Varies by setting | Seasonal | Part or all of the night | Near the home, in open air spaces |