Surveillance and response for high-risk populations: what can malaria elimination programmes learn from the experience of HIV?

A literature review was conducted to identify evidence of high-risk populations in malaria by searching PubMed using the terms “malaria + elimination + high + risk + populations”. HIV literature was selected by reviewing the series of guidelines published by UNAIDS/WHO Working Group on Global HIV/AIDS and STI Surveillance [22] as well as studies illustrating approaches known to the authors.

In all settings, individual risk of malaria infection is determined by environmental factors that influence the density of competent anopheline mosquitos, location-specific vector behaviour, and human behavioural factors that increase an individual’s exposure to infectious bites. In many elimination settings, residual transmission exists due to anopheline species that exhibit outdoor feeding and resting behaviour (exophagy and exophily), which often coincides with outdoor human behaviours during biting hours [23, 24]. While long-lasting insecticide-treated nets (LLINs) and indoor residual spraying (IRS) are effective for more endophagic and endophilic anopheline species, where high coverage of LLINs and IRS has been achieved, programmes often observe behavioural shifts towards increased outdoor feeding and resting [25‐27], as well as increased proportional abundance of more exophilic species such as Anopheles arabiensis [28]. In much of Asia, and southeast Asia in particular, malaria transmission persists due to forest-adapted vectors, such as Anopheles dirus, which exhibit outdoor biting behaviour, transmit Plasmodium knowlesi between macaque monkeys and humans, and are very difficult to control [29, 30].

Economic forces are a major factor responsible for human movement and bring people into closer contact with vectors through migration, forest work or specific livelihood activities. Table 1 summarizes some of the risk factors identified in countries moving from controlled low-endemic malaria to elimination (“malaria-eliminating” countries) [31] (Table 1). Several occupational groups have been identified as risk populations in different elimination settings, including laborers in fishing and agriculture, military, mining, construction, oil and gas, and general forest work. In southeast Asia, rubber plantation workers are a specific risk group predicted to increase in coming years, and are often highly mobile [32]; these groups and other migrant forest workers often have poor social integration due to language and cultural differences and occasionally, illegal activity [33]. Importation of cases by migrant labourers moving between high and low transmission settings, both within and between countries, can challenge elimination efforts. For example, seasonal farm work facilitates importation of cases between regions of Ethiopia [34]. Following elimination of local transmission in Sri Lanka, cases were imported by fishermen returning from Sierra Leone and military personnel returning from South Sudan and Haiti [8]. Cases have been imported to China by gold miners returning from Ghana [35]. Similarly, migrant laborers have frequently been found to be a key driver of incipient HIV epidemics [36].

Much remains unknown regarding how to best access the malaria risk populations identified to date for purposes of surveillance and response: the extent to which they may be captured by present surveillance and response activities; how to disseminate interventions with high coverage; and how to accurately track transmission and monitor intervention coverage. Some risk populations that have been more broadly defined—such as “tourists”, “foreign travellers” and “migrants” [37], “rural, indigenous populations” [1, 38, 39] and particular ethnic groups [6, 40]—require sharper definition to allow for meaningful targeting in specific elimination settings. Malaria programmes have begun to experiment with innovative strategies to access high-risk populations, often drawing on tools developed in the context of HIV; for example, screening at border crossings [41] and refugee camps [42], venue-based surveys [34], respondent-driven sampling (RDS) surveys [43, 44] and interviewing the social contacts of recent cases to identify behavioural risk factors [45]. Yet, such strategies have not yet solidified into routine practice. Improving surveillance and response for high-risk populations is a high priority for malaria eliminating countries, and is especially urgent in southeast Asia where MMPs are thought to influence the spread of artemisinin resistance [46].

While some similarities exist, HIV and malaria are characterized by distinct transmission mechanisms and risk factors that impact the effectiveness of potential surveillance and response approaches for high risk populations: malaria risk is determined by human-vector contact at specific times in geographic areas where specific vectors are endemic, while HIV is transmitted person-to-person primarily through sexual intercourse, drug injection, and blood transfusion. Nonetheless, both HIV programmes and malaria elimination programmes face the similar challenge of identifying and accessing relatively small high-risk populations that are key to continued transmission, which are at increased risk from specific behaviours or occupations, and yet which may be systematically missed by passive surveillance and household surveys. In the malaria context, these populations are often difficult to access due to cross-border mobility, high rates of asymptomatic infection, frequently being away from their home due to forest or other work, and poor social integration in the case of migrant workers. These factors additionally make it difficult to achieve high coverage of interventions and to accurately track trends in infection prevalence and prevention coverage.

In HIV, guidelines for Second Generation Surveillance (SGS) released in 2000 were a response to these challenges [47, 48]. Data from “first-generation” HIV surveillance—case reporting and limited prevalence studies—were seen as inadequate to form a complete picture of transmission in the presence of hard-to-reach, high-risk populations.

The SGS guidelines included a series of key principles to guide surveillance systems (Fig. 1). One change was expanding the scope of surveillance, in part by encouraging HIV programmes to examine a range of “markers” of potential risk, such as data on other sexually transmitted infections and tuberculosis. More relevant to malaria is the SGS principle that surveillance systems gather and analyze behavioural data. This is primarily done in two ways. First, passive surveillance expands to describe the distribution of risk behaviours among passively detected cases by recording whether they engage in known risk behaviours (e.g., sex work or, in malaria, forest work) on case report forms. Second, HIV programmes conduct behavioural surveys (these surveys are called "behavioural surveillance surveys" or BSS, because they are used for tracking trends over time) [49]. Behavioural surveys gather information on the target population’s knowledge and understanding of risk, the specific practices that lead to risk, the use of preventive measures, and treatment-seeking. Behavioural data thus allow for better understanding of how transmission is occurring, identify gaps in prevention coverage and treatment services, and provide early warning of upticks in transmission (if risk behaviours increase or prevention coverage declines). They can also help explain trends in case data and prevalence.

Many countries routinely conduct integrated biological and behavioural surveys (IBBS), which are similar to malaria indicator surveys (MIS), yet generally target a specific risk group, collect biological specimens to assess prevalence (and often incidence) and include a linked behavioural survey. SGS also includes studies to estimate the size of high-risk populations, often conducted together with BSS and IBBS to reduce costs [50]. BSS and IBBS utilize sampling methods appropriate to the target population, overcoming the chief limitation of passive and household surveillance to provide unbiased estimates among hard-to-reach, high-risk populations, for example, by sampling sex workers at sex work locations and through peer networks [51].

New tools have been introduced to assist countries synthesize data from these multiple sources in order to prioritize populations and locations and to define surveillance and intervention strategies; these include the pre-surveillance assessment (PSA) [52], public health triangulation [53], and integrated epidemiologic profile [54].

A key concept of SGS for HIV is that surveillance components should be adaptive to changing transmission patterns (Fig. 2a). For example, in countries where HIV transmission is primarily “concentrated” among high-risk populations, it is recommended that HIV programmes regularly conduct studies to estimate the size of these groups and IBBS in order to track prevalence of infection, intervention coverage, and to gather additional demographic and behavioural data to improve the targeting of interventions. In addition, sentinel surveillance is also recommended, typically at antenatal care (ANC) facilities, to provide early warning of expansion of transmission beyond high-risk groups. When HIV transmission has become widespread in the general population (“generalized” epidemics), it is recommended that countries expand ANC sentinel surveillance nationally and conduct IBBS in the general household population (i.e., by household surveys). Even in generalized epidemics, targeted surveillance of high-risk populations continues as targeted interventions can exert considerable impact [55, 56]. Regardless of the transmission pattern, countries should continually improve access to testing and passive surveillance.

Similar to HIV, at higher levels of transmission, malaria surveillance systems rely primarily on passive surveillance supplemented by large cross-sectional surveys such as an MIS. As transmission levels decline, the World Health Organization (WHO) recommends a shift in the scale of surveillance from reporting aggregate data on malaria morbidity and mortality at the health facility or district level to more rapid, finer scale case-based surveillance, which requires rapid reporting and investigation of individual cases and geographic foci. Detailed case and foci investigation is important for classifying cases as local or imported, determining the source of transmission, and planning responses. These changes are a necessary response to the changing epidemiology of malaria at low transmission, which is more likely to be imported, and occur more focally, seasonally and in older demographic groups. However, targeted surveillance of highly mobile high-risk populations continues to be limited within this framework. While reactive case detection (RCD) is frequently adopted to target active surveillance and response to areas with higher local transmission [1], other risk-based surveillance components to actively target high-risk populations are only rarely incorporated into malaria surveillance.

The first step of the surveillance cycle is to assess the overall surveillance system’s strengths and weaknesses, based on current understanding of how and where transmission is occurring, and reorient surveillance strategies as needed. Key questions include: Which population subgroups, in which areas, are most affected?; Which are key drivers of transmission?; Are these subgroups adequately captured and characterized by existing surveillance activities (e.g., passive surveillance, prevalence and behavioural surveys, sentinel surveillance)?; If not, what new data and strategies are needed? In HIV this assessment is called “pre-surveillance assessment” (PSA) because it is generally undertaken prior to planning a new round of targeted surveillance studies nationally [52]. PSA could be a valuable tool for malaria elimination programmes as they endeavor to identify and address high-risk populations. In malaria contexts, PSA could result in decisions regarding how to strengthen passive surveillance (e.g., adding behaviourial data items to case reporting forms, engaging more private sector providers in reporting), identifying new high-risk populations where targeted studies and/or size estimates are needed, and, overall, determining which populations and areas should be prioritized by surveillance to achieve greatest impact.

A coordinating body (often organized as a working or advisory group) is often established to guide the PSA process due to the many actors typically involved in supporting prevention and surveillance activities in HIV high-risk populations. Although surveillance decisions are ultimately made by a unit in the health ministry, the coordinating body helps to ensure the data collected by the surveillance system meet the country’s needs, ensures widespread use of data, and makes certain the system is adequately funded. Malaria programmes may find such a structure helpful as they work increasingly with MMPs and occupational groups at elevated risk. During PSA, the coordinating body can help ensure the scope of the assessment is sufficiently wide-reaching, improve access to key informants and data sources, and help interpret the data.

Formative assessment—a narrower process to gather information needed to plan one particular study [59]—is typically conducted as part of the PSA as it becomes clear that targeted studies may be needed. PSA’s more high-level questions about prioritizing populations and determining surveillance strategies, as well as the narrower operational questions for study planning, are answered in part by a rapid “on-the-ground” field assessment, which includes key informant interviews, focus groups, mapping of risk contexts and other qualitative data collection methods. Key questions for field assessment include: Is the high-risk population large enough to warrant a targeted study? How should the population be defined for surveillance purposes? What sampling method is most appropriate? Other themes appear in Fig. 4.

As in HIV, malaria programmes can benefit from a wide-reaching PSA process. The data review should draw on all sources of information that could provide insight on populations potentially at elevated malaria risk, beginning from passive surveillance, but also considering health facility records, death registries, demographic health surveys, entomological surveillance data, vector control and other programme data from governmental and non-governmental organizations (NGOs) (e.g., military, agricultural, mining, logging) that work with the potential high-risk groups, and available qualitative studies and media reports to build a more complete picture of transmission and risk. A recent effort to characterize risk among MMPs in Cambodia provides a good example of data synthesis by drawing on diverse data sources [33, 60]. A recent WHO manual describes data sources and data collection methods that may be relevant to MMPs in the Greater Mekong Subregion [61]. Similarly, field assessment should query a broad spectrum of actors, such as community leaders, organizations with knowledge of the populations of interest, health workers, and members of the suspected risk populations, thus providing an opportunity to engage with affected communities. Contact tracing of malaria cases who report recent local travel or forest work can also help to develop hypotheses regarding behavioural risk factors and identify other individuals with whom they travelled or worked [45].

Following PSA, more rigorous studies to estimate the prevalence of malaria parasite infection in suspected risk populations will likely be needed because evidence from PSA tends to be based on secondary analysis and qualitative methods. Case–control studies can effectively identify risk factors and are recommended by the WHO for malaria elimination settings with low case numbers [16, 62‐65]. However, because case–control studies typically include individuals diagnosed at health facilities or sentinel sites, inference may be limited to symptomatic malaria. Patterns in service utilization may also introduce bias (e.g., if MMPs have limited access to public facilities). To overcome these limitations, case–control studies could be nested within active surveillance, such as RCD or in the context of a targeted parasite survey.

In HIV, IBBS are the standard tool to assess infection prevalence and behaviours in high-risk populations and to track these over time given high rates of asymptomatic infection barriers to testing [22]. Estimates of infection prevalence from IBBS are compared to a general population estimate to establish evidence of increased risk. For malaria, this could be done by comparison to targeted household surveys in potentially high-risk areas, potentially reducing costs by using lot quality assurance sampling, or by comparison to easy access groups [66].

Achieving appropriate targeting and high levels of coverage are often the key challenges of interventions in high-risk populations [94]. To improve trust, acceptance and effectiveness, engaging with communities is critical to HIV interventions. Planning should include identifying community organizations and leaders, which often already have the know-how to access risk populations, and may hold influence on the population’s receptiveness to new initiatives. Including members of the target population as project coordinators, interviewers, trainers, health or peer educators is a best practice in HIV. At the same time, those planning interventions should be aware of divisions when affiliating with any particular group or individual.

Malaria programmes’ conventional approaches to disseminating interventions—through household visits, health facilities, and community health workers—may be effective when risk and/or risk behaviours are widespread, and high-risk individuals tend to develop symptomatic infections, are accessible at their households and have good access to health care. If instead risk clusters within workers of an organization, then offering workers regular access to prevention, screening, and treatment may be more efficient. To extend reach beyond the often small subset of individuals linked with community organizations, HIV interventions have adopted approaches that parallel sampling strategies. For example, venue-based outreach often begins by mapping of risk locations [95, 96]. As in RDS, peer-driven interventions (PDIs) enlist high-risk individuals to provide prevention information to their social contacts [97], thus harnessing trust and peer pressure to expand reach, and often employing incentives to improve participation and referral [98, 99]. Social network strategies have proven successful outside of HIV; for example, exposing nominated friends of random villagers to a nutritional programme increased communities’ overall uptake compared to targeting random villagers [100]. Venue-based and PDI approaches have also been combined effectively, by initiating peer-referral with individuals encountered at high-risk venues [101]. In malaria, peer educators could be enlisted to disseminate information and/or preventive items and refer peers to testing and prevention programmes; dissemination of larger commodities, such as LLINs, poses logistical challenges but could be explored. Lessons learned regarding PDIs in the context of HIV [97‐99, 102‐105] are shown in Fig. 7.