Introduction Chagas disease still imposes a heavy burden on most Latin American countries, with about 10–12 million people infected by Trypanosoma cruzi [1], [2]. Multinational control initiatives have since the early 1990s drastically reduced prevalence and incidence, mainly through insecticide-based elimination of domestic vector populations (blood-sucking bugs of the subfamily Triatominae) [3] and systematic screening of blood donors with highly sensitive serological tests [1], [2], [4], [5]. In spite of these advances, vector-borne transmission is estimated to cause about 40,000 new infections per year [6]. Reinfestation of treated households by native vectors as the residual effect of insecticides vanishes is the most likely mechanism underlying such persistent transmission [7]. Similarly, outbreaks of acute Chagas disease have been attributed to the contamination of foodstuffs by infected adult (i.e., winged) triatomines that invade premises where food is processed or stored [8]–[12]. In Amazonia and other humid forest ecoregions, where the bugs rarely colonise inside houses, endemic, low-intensity transmission seems also mediated by adventitious, household-invading triatomines [13]–[15]. In addition, there is growing concern that insecticide-resistant vector populations, such as those detected in southern South America [16], [17], may threaten effective disease prevention. This rapid overview shows why sustained Chagas disease control is believed to require some sort of longitudinal, long-term surveillance system capable of detecting and eliminating household infestation foci [1], [18]. Surveillance typically relies on the periodical inspection of households by trained personnel. Active vector searches are performed with or without the aid of chemical ‘flush-out’ agents such as low-dose pyrethroid dilutions, and infestation foci are eliminated by insecticide spraying when discovered [18]. However, detecting the vectors can be difficult, particularly when only small populations occur within or around households. In fact, vector colonies are expected to become rarer and smaller as control programmes proceed, and managers are progressively less prone to fund costly active surveillance resulting in few detection events. A number of vector-detection devices have been designed in an attempt to enhance surveillance; most consist of boxes that triatomines can use as refuges or of paper sheets or calendars where the typical faecal streaks of the bugs can be identified [19]–[27]. Such ‘sensing devices’ are placed within households or in annex structures and checked periodically for bugs or their traces, supposedly reducing the costs of surveillance while retaining adequate sensitivity [26]–[29]. Finally, and since the early vector control trials, there has been a perception that resident householders may have better chances of discovering bugs in their own homes than a visiting team searching the house for a few minutes every several months [30]–[32]. ‘Community participation’ in entomological surveillance gained extra momentum with the Declaration of Alma Ata [33], [34], which “…encouraged approaches to health care that incorporated community participation and community development” (ref. [34], p. 1). Experiences involving community participation in Chagas disease control have been described in several settings across Latin America [18], [30], [31]; they seem to converge towards an encouraging overall picture, and the Chagas disease example has accordingly been praised in several subjective reviews (e.g., [35], [36]). However, the effectiveness of these diverse strategies for Chagas disease vector surveillance, including community participation, has not been thoroughly and objectively assessed at the continental scale. With the aim of filling this gap, we systematically reviewed the published evidence on this issue, tackling specifically the following major questions: (i) How common and important is the phenomenon of house reinfestation by triatomine bugs after control interventions?; (ii) How effective are different vector surveillance strategies at detecting infestation/reinfestation foci?; (iii) To what extent have community participation and empowerment been effectively promoted?; and, finally, (iv) Can available strategic options be condensed in overarching recommendations for surveillance that apply across the highly diverse ecological and social-cultural settings where the problem is present? Methods The review protocol is available upon request from the corresponding author. This review was carried out in the context of a collaborative project led by the Inter-American Development Bank, and was not formally registered. We searched Medline, ISI Web of Knowledge, Scopus, LILACS, and SciELO; the major query argument was “Triatomin* AND (Control OR Surveillance)”. Searches retrieved records from 1948 to 2009, including additional documents identified by searching bibliographies and in the authors' records. This search strategy aimed at recovering documents describing vector control interventions, with or without surveillance, so that post-control reinfestation trends could also be assessed. Only documents describing field interventions aimed at the control and/or surveillance of domestic Chagas disease vectors were included in the full review process. Descriptive (non-intervention) reports, results of research with laboratory or experimental vector populations, expert reviews, and opinion or commentary pieces were either excluded or used only for the introduction and/or discussion. We were particularly interested in comparing strategies involving institutional (by professional staff) or participatory surveillance. We also compared alternative methods for vector detection, including active searches, vector-detection devices, and community participation. Major outcomes included household infestation/reinfestation indices (or, in some cases, bug catches) and vector detection rates. Inclusion/exclusion of documents was assessed independently by ARdA and FA-F, and discrepancies resolved by consensus. Figure 1 presents the flow diagram of the review process. Data were independently extracted by ARdA and FA-F using predefined data fields inspired by the Guide to Community Preventive Services [37] (www.thecommunityguide.org) and including study quality indicators. FA-F revised data extraction results and resolved inconsistencies by re-checking the original documents. The following items were considered: (1) study classification (study design, intervention components, whether or not the intervention was part of a broader initiative, outcomes); (2) descriptive information, including (2.i) description of the intervention (what was done, how, where and by whom it was done, theoretical basis of the intervention, types of organisation involved, whether or not there was any intervention in a control group), (2.ii) study characteristics (place, time, population, settings, outcome measurement, whether or not there was a measurement of exposure to the intervention), (2.iii) results (primary results, sample and effect sizes), and (2.iv) applicability in settings other than the actual study one (direct and indirect costs, harms and benefits, implementation process, and whether the community participated at each stage of the process – design, pre-implementation, effecting, and evaluation); and (3) study quality, including quality of descriptions, sampling (universe, eligibility and selection of participants, sample size, potential sampling biases), effect measurements, data analyses (statistics, confounders, repeated measures or other sources of non-independence), and interpretation of results (rate of adherence, control and assessment of potential confounders and sources of bias). Relevant references and other details deemed important were also recorded. The protocol required extracting detailed demographic data about intervention and control or indirectly affected populations. Such information was however absent from or incomplete in most studies; this, together with the fact that the outcomes of primary interest refer to households, not individual people, led us to exclude these items from the protocol during the course of the review. 10.1371/journal.pntd.0001207.g001 Figure 1 Flow diagram of the systematic review process. The often important morphological, ecological and behavioural differences among triatomine bug species [3], combined with the likely sensitivity of results to study-specific (methods, research team performance) and site-specific conditions (vector density, household building materials and structure), led us to avoid estimating meta-analytical summary effects from different reports. Inadequate design and/or reporting of several studies were further factors hindering meta-analysis. When enough information was given in the original reports, we nonetheless re-analysed data from studies comparing control strategies (in terms of household infestation rates) and vector detection techniques (in terms of detection rates). Whenever possible, we used McNemar's tests for correlated proportions [38], with odds ratios (OR) estimated as the ratio of discordant results. When independence of observations was likely, or in the absence of complete data on repeated observations, ORs were estimated from standard contingency tables [39]. Approximate OR 95% confidence intervals (95%CI) were calculated by assuming normality of log-odds [39]. The VassarStats online facility (http://faculty.vassar.edu/lowry/VassarStats.html) and Microsoft Office Excel® spreadsheets were used for the analyses. Results Overall results Database searches retrieved 1,342 candidate documents; elimination of duplicates yielded 858 unique records (Figure 1) in English, Spanish, or Portuguese. Assessment of titles and abstracts yielded five groups: (a) documents apparently describing control and/or surveillance interventions (236 records), (b) non-intervention studies, (c) studies with laboratory or experimental vector populations, (d) subjective reviews and opinion pieces, and (e) reports clearly irrelevant to our review. Evaluation of group (a) documents against inclusion criteria identified 93 reports for full data extraction [Supporting Information, List S1]; of the remaining 143 (plus several additional references), 26 studies [Supporting Information, List S2] were also used for partial quantitative assessments, and the rest were considered as supplementary sources of qualitative information for the introduction and/or discussion. The spatial and ecological coverage of our review is represented in Figure 2. Only 11 randomised trials [40]–[50] were identified, with just one crudely assessing a community-based intervention [50] and four describing different aspects of the same trial [44]–[47]. Over half of the studies dealt directly or indirectly with different strategies for household-level vector surveillance. Interventions ranged from insecticide spraying (the most frequent) to educational activities, with a few studies describing alternative control approaches such as environmental management [51]–[58] or insecticide-treated materials [48], [49], [59]. Most studies measured intervention effects as reductions in household infestation rates (through entomological surveys) or as vector detection rates (through detection records). While the quality of the descriptions was generally adequate, analytical procedures were often dubious; for instance, albeit many studies describe results in which the same sampling units were assessed more than once (e.g., before-after, time-series) or by more than one method (e.g., vector-detection studies), only a few apply statistical tests suited for repeated measures or other sources of non-independence of observations. 10.1371/journal.pntd.0001207.g002 Figure 2 Geographical-ecological coverage of studies on Chagas disease vector control and surveillance. Study site locations (black dots) are overlaid on the World Wildlife Fund ecoregional map of Latin America (available with detailed ecoregion legends at www.conserveonline.org/docs/2001/06lac_ecoregions.jpg). Collaborative efforts involving both academic institutions and official public health agencies were common (∼70% of studies), a typical historical trait of Chagas disease vector control [60]. Even though sustainability was discussed in several documents, detailed assessment of the costs (monetary and not) and potential unintended benefits and harms was rare. Forty-eight reports described some sort of ‘community participation’ in the intervention; however, none of them explicitly stated that participation took place at the design stage, and only three describe a participatory evaluation process [47], [58], [61]. In contrast, local residents helped carry out the intervention in 45 studies, mainly by reporting vectors caught in their homes; in 20, the community was also involved in the pre-implementation phase. Control effectiveness and the role of surveillance Since Carlos Chagas historic paper [62], vector control has become the cornerstone of primary Chagas disease prevention [60], [63]. Pioneering attempts involved chemical (including cyanide gas) and physical means (including flamethrowers) [64]. The failure of DDT in controlling triatomines was followed by substantial optimism when HCH (lindane) proved successful in early trials in Brazil [65], [66], Argentina [67], and Chile [68]. The effectiveness of insecticide-based control kept improving as new chemicals and better formulations, with longer residual effects and lower toxicity, were introduced [40]–[42], [45], [69], [70]. Synthetic pyrethroids are now widely used and continue to be very efficient [71]–[75]; yet, recent research suggests that resistance may be widespread among some Triatoma infestans populations [16], [17], and insecticides are less effective in peridomestic environments [43], [76]. The top-quality report (in terms of sample size, design, and data treatment) we retrieved shows that peridomestic T. infestans foci reappear quickly after spraying (albeit with lower-density colonies) and that standard deltamethrin application with manual sprayers performs better than more sophisticated techniques [43]. Table 1 summarises the results of major reports on Chagas disease vector control [5],[18],[44],[57],[61],[63],[71]–[73],[77]–[113]. Overall, these studies unequivocally show that household insecticide spraying has successfully reduced infestation rates throughout Latin America, but also that reinfestation of dwellings by native vector species is common, spatially widespread, and temporally persistent. In many cases, the elimination of introduced populations was closely followed by the occupation of vacant niches by ‘secondary’ vector species, suggesting that the former had displaced the latter upon introduction [114], [115]. 10.1371/journal.pntd.0001207.t001 Table 1 Chagas disease vector control interventions: effectiveness, reinfestation trends, and the replacement of introduced species by native vectors. Ref. Comparison Intervention Vectors Setting Units, size Main results, comments and caveats [77] Before-after HCH Ti*, Pm Brazil (Cerrado, Bahia Interior Forests) Infestation rates, 324 DUs Infestation odds ∼6 (3 to 12) times lower after treatment; treated DUs near non-treated localities were ∼5 times less protected. (Analyses assume observations in each DU and time-point are independent) [78] Time-series (1951–64) HCH yr 6–8 Ti*, Pm Brazil (Cerrado, Bahia Interior Forests) Capture events by control agents and bugs captured by control agents Median annual capture events before-during-after treatment: Ti, 95-13-24; Pm, 31-14-36.5. Median number of bugs captured before-during-after treatment: Ti, 4,405-1,802-274; Pm, 138-72-186. (No information on number of DUs studied each year) [79] Time-series (1950–54; 1960–69) HCH Ti*, Pm Brazil (Alto Paraná Atlantic Forest, Cerrado) Number of bugs captured in DUs Median annual capture (range) 1950–54: Ti, 1,330 (167–1,850); Pm, 14 (0–775). Median annual capture (range) 1960–69: Ti, 27 (3–440); Pm, 1,506 (678–3,741). (No information on number of DUs studied each year) [80] Before-after HCH Ti*, Ts, Pm Brazil (Cerrado) Vector presence, ∼500 localities Ti virtually disappears; Ts persists in DUs of ∼45% of localities; Pm presence rises from 26% to 41% of localities [63] Time-series (1983; 1986–99) Mainly Deltamethrin Ti*, several native spp. Brazil (several ecoregions across the country) Number of bugs captured by control agents per yr countrywide Ti falls from >84,000 (in 1983) to 60,000 in 1953 to 0 in 2000, with the last focus (131 bugs) eliminated in 1999; Ts reaches a maximum of >114,000 in 1968, then steadily decreases to ∼7,000 bugs/yr from 1990 on; Pm reaches a maximum of >10,500 in 1968, then decreases to ∼2,800 bugs/yr in the 80s, ∼1,100 in the 90s, and ∼500 bugs/yr in 2000–2008. The number of DUs searched each year varied markedly: >600,000/yr up to 1973, ∼450,000/yr 1974–84, ∼20,000/yr 1985–88, and 35% up to 1971 to 25% in 1972, ∼15% in 1973–76, 5–10% in 1974–84, and 30% in the last assessment. (Approximate values taken from Figure 1A in the reference) [96] Before-after Deltamethrin Ti Argentina (Dry Chaco) Infestation rates, 533 DUs initially; 89 localities Pre-treatment infestation rate: 48.2%; 1 yr later, 383 DUs searched (only peridomicile) and 108 found infested (28.2%). Infestation of localities: 53% before, 39% after (McNemar OR 0.5, 95%CI 0.3–1.02) [18] Time-series (1984–2006) Mainly Deltamethrin, fumigant canisters Ti Argentina (Dry Chaco) Infestation rates, ∼300 DUs Pre-treatment infestation 88%; 6 mo after 0%; recovery to pre-treatment levels in 5–7 yr; new interventions (community-based surveillance and selective control) reduce infestation to 25% 4 yr later; thereafter, and for 7 more yr, infestation remains ∼10% on average [5], [97] Time-series (1980–2000) National control programme Mainly Ti (partly*) Argentina (all ecoregions north of parallel 46S) Overall DU infestation rates ∼30% infested DUs in 1980; >6% in 1992; 100,000 DUs/yr between 1991 and 2000; >820,000 DUs were under surveillance by 2000 [97] Time-series (1964–2000) National control programme Mainly Ti (partly*) Argentina (all ecoregions north of parallel 46S) Province-specific DU infestation rate classes The percentage of provinces with infestation rates >20% fell from 68.2% in 1964 to 60% (1982), 58.3% (1987), 22.2% (1992), and 5.5% (2000); for provinces with rates below 20%, the figures were 31.8%, 40%, 41.7%, 77.8%, and 94.4% for the same years. (N = 22, 15, 12, 18, and 18 provinces surveyed in each evaluation year) [57], [72] Before-after and follow-up at 6-mo intervals for 18 mo Lambda-cyhalothrin, housing improvement, and both combined Ti, Ts Paraguay (Humid Chaco) Infestation rates, 185 DUs initially Houses: pre-treatment: 42.3% infested; post-treatment: insecticide alone 2.4%, insecticide+housing 16.4%, housing improvement alone 3.4% (all effects reported as significant after McNemar tests). Peridomiciles: initially 13.9%; after treatments, 0%, 3.5%, and 1.7%, respectively (only the combined treatment reported as significant after McNemar tests). Infestation recovered to >6% in 18 mo. Housing improvement costs were >24 times higher than those of insecticide [98] Time-series (1977–2000) Mainly pyrethroids Mainly Ti, Ts Paraguay (Dry and Humid Chaco, Alto Paraná Atlantic Forests, Paraná Flooded Savanna) DU infestation rates Overall infestation fell from 39.5% (1977) to 14% (1985) and 10% (1996); assessment of ∼170,000 DUs in 1999–2001 yielded an infestation rate of 0.73%, but much higher rates (∼37%) are common in indigenous communities of the Chaco [99] Before-after (2 surveys) National control programme Ti*, Trv Uruguay (Uruguayan Savanna) Infestation rates, ∼240,000 DUs Pre-intervention: overall rate 2.4% (up to 6.3% in 1 department); by 1992, overall 0.5% (up to 2.7%); by 1999, overall rate 0.1% (up to 0.7%). Ti was virtually eradicated from the country [100] Before-after HCH (2 rounds) Ti* Chile (Valdivian Temperate Forests, Chilean Matorral) Infestation rates, >32,700 DUs in 199 localities Observed infestation: pre-treatment 3%, post-treatment 0.3%. Infestation as reported by dwellers: pre-treatment 18.7%, post-treatment 3% [101] Time-series (1982–95) “Pyrethroids”, with no specification Ti* Chile (Chilean Matorral) DU infestation rates, ∼480 DUs per assessment Pre-intervention (1982): 73.3% of DUs infested; 1992, 24.1%; 1993, 3.9%; 1994, 2.8%; 1995, 4%. (Community-based surveillance started in 1992 after a massive spraying campaign [1988–91]) [102] Before-after National control programme Ti* Chile (Valdivian Temperate Forests, Chilean Matorral) DU infestation rates Pre-intervention overall rate was >35% in 1980; systematic control and surveillance from 1993 onwards reduced infestation to 60% by NR. (Unclear data presentation precluded further analyses) [32] NR vs. AS Mainly Ts, Pm Brazil (Serra do Mar Coastal Forests, Alto Paraná Atlantic Forests, Cerrado) Detection events in variable DU numbers from 1990 to 1995 Houses: 1990–91, OR 7.2, 95%CI 6.1–8.6, N>31,000; 1992–93: OR 5.8, 95%CI 5–6.7, N>47,500; 1994–95: OR 4.1, 95%CI 3.5–4.8, N = 36,500. Peridomiciles: 1990–91, OR 2.6, 95%CI 2.4–2.9, N∼28,000; 1992–93: OR 2.6, 95%CI 2.4–2.8, N∼43,500; 1994–95: OR 2.15, 95%CI 1.96–2.4, N>33,600. (Analyses assume that all observations are independent, which was likely the case in most instances) [132] NR vs. ASfo Ti Argentina (Dry Chaco) Detection events in 98 DUs (1993–96) Houses: McNemar OR 7, 95%CI 2.1–23.5. Peridomestic areas: McNemar OR 0.2, 95%CI 0.08–0.5 (i.e., ASfo performed better than NR at detecting peridomestic infestation) [107] NR vs. AS and DDgn Mainly Rp, also Tmac, Pg, Rpic Venezuela (Llanos) Detection events in 550 DUs NR vs. AS: McNemar P 1 indicate a positive effect of the first method in the comparison; see Table 2 for details. Vector-detection devices Several ‘passive’ vector surveillance methods have been devised and tested over the years. As defined here, they differ from the traditional, ‘active’ surveillance approach in that control programme agents do not search the whole residence to determine whether it is infested; instead, they rapidly check for bugs (or their traces) in a ‘detection device’. Table 3 summarises the main results of major comparative studies [20]–[22], [26]–[28], [130], [132], [134]–[140]. In general, the sensitivity of vector-detection devices does not seem to be superior to that of active searches, but (i) both methods appear to complement each other, with only one of them revealing infestation in many instances (see also ref. [141]), and (ii) the costs of the passive approach are, in general, lower (but see ref. [28]). Several studies with small sample sizes favour sensing devices, whereas the results of larger trials tend to show that they perform equally or worse than active searches (Figure 4). The evidence in relation to vector-detection devices remains therefore inconclusive, and further research is needed; below (Conclusions and outlook) we provide methodological suggestions to this end. 10.1371/journal.pntd.0001207.g004 Figure 4 Detection of Chagas disease vectors by vector-detection devices vs. alternative methods: estimated odds ratios and 95% confidence intervals. AS, active searches by vector control staff (ASfo, using a flushing-out agent; ASkd, using full insecticide application to ‘knock-down’ the bugs); DD, vector-detection devices (DDgn, Gómez-Núñez boxes; DDmb, ‘María’ boxes; DDb, box; DDps, paper sheet; DDp, plastic boxes); (p), results in the peridomestic area; the reference number and sample size are indicated in parentheses; studies were ranked by mean effect size; effects are significant at the 95% level when the CI does not cross the dashed line; point estimate values >1 indicate a positive effect of the first method in the comparison; see Table 3 for details. 10.1371/journal.pntd.0001207.t003 Table 3 Chagas disease vector surveillance: performance of different vector-detection devices across regions and triatomine species. Ref. Comparison Vectors Setting Units, size Main results, comments and caveats [135] DDgn vs. AS (nd) Rp Venezuela (La Costa Xeric Shrublands, Llanos) Detection events, 42 DUs, 5 monthly assessments Overall, DDgn were about 7.5 times more likely to detect infestation than AS (95%CI ∼1.7–33) (Approximate values taken from detection rates averaged over assessments) [136] DDgn vs. AS (nc) Ti Brazil (Alto Paraná Atlantic Forests, Serra do Mar Coastal Forests) Detection events, 27 houses and peridomestic annexes McNemar OR 1.25, 95%CI 0.34–4.7; in 5 cases, only DDgn detected infestation, and in 4 cases only AS did so [137] DD vs. AS (nc) Ts Brazil (Cerrado) Detection events, 72 houses and peridomestic annexes McNemar OR 0.24, 95%CI 0.09–0.63; in 21 cases, only AS detected infestation, and in 5 cases only DD did so [130] DDgn vs. AS (c) Ti Chile (Valdivian Temperate Forests, Chilean Matorral) Detection events in 43 DUs known to be infested by combining AS, DDgn and NR McNemar OR 6, IC95% 1.3–26.8. This positive effect of DDgn on detection only became apparent after several weeks of DDgn operation [138] DDgn vs. ASfo (nc/c) Ti Brazil (Cerrado, Atlantic Dry Forests) Detection events, 104 DUs DDgn performed significantly worse than ASfo: McNemar OR 0.06, 95%CI 0.014–0.25 [139] DDgn vs. AS (nc/c) Pm Brazil (Bahia Interior Forests) Detection events, 247 DUs DDgn performed significantly worse than AS: McNemar OR 0.26, 95%CI 0.11–0.6 [20] DDmb vs. ASfo (nc) Ti Argentina (Dry Chaco) Detection events, 38 DUs ASfo performed slightly better than DDmb (McNemar OR 0.5, 95%CI 0.13–2); Wisnivesky-Colli et al. [29] suggest that DDmb costs are 4 times lower [28] DDmb vs. AS (c) Ts Brazil (Atlantic Dry Forests, Caatinga, Cerrado, Bahia Interior Forests) Detection events, 225 DUs Infestation rates ascertained with DDmb were about one order of magnitude lower than those reported by control programme agents using AS. AS-based surveillance costs were estimated to be ∼1/4 of those of the DDmb-based strategy, mainly because of the need for several visits per year to check the devices [21] DDsf vs. DDmb (nd) Ti Argentina (Dry and Humid Chaco) Detection events, 63 DUs McNemar OR 14, IC95% 1.8–107. DDsf cheaper than DDmb [27] DDb and DDps vs. ASfo (nc) Ti Argentina (Dry Chaco) Detection events, 45 DUs DDb vs. ASfo: McNemar OR 9, 95%CI 1.14–71. DDps vs. ASfo: OR 3.5, 95%CI 0.73–16.9 [132] DDb vs. ASkd (c) Ti Argentina (Dry Chaco) Detection events, 60 DUs After 1 yr of DD operation: McNemar OR 4.5, 95%CI 1.5–13.3. After 2 yr of DD operation: McNemar OR 1.9, 95%CI 0.7–4.7. The results suggested that AS sensitivity depended on vector density – as measured by the number of faecal streaks in DDb. A previous trial [141] suggested that ASfo perform better than ASkd (McNemar OR 5, 95%CI 1.5–17.3), but bug removal by ASfo may have distorted subsequent ASkd results [134] DDp vs. AS (nc) Ti Argentina (Dry Chaco) Detection events, 56 peridomestic structures After 11 mo of DDp operation: McNemar OR 6.3, 95%CI 1.9–21.4. The cost of DDp was also lower [22] DDtb vs. AS (nc) Ti Argentina (Dry Chaco) Detection events, 51 peridomestic structures No differences in performance, but DDtb cost said to be about 12–20% that of AS [26] DDgn and DDps vs. AS (nc) Rec Peru (Peruvian Yungas, Tumbes-Piura Dry Forests) Detection events, 207 DUs in 19 localities DDgn vs. AS: McNemar OR 11.1, 95%CI 3.3–33.3; in 3 DUs infestation was only detected by AS, while in 33 DUs only the DDgn revealed bug presence. DDps and AS were similarly sensitive (McNemar OR 1.2, 95%CI 0.5–2.7) but complemented each other (infestation detected by just one method in 22 DUs) [140] DDmb vs. AS (nc) Mainly Td Nicaragua (Central American Dry Forests) Detection events, 99 DUs in 2 communities DDmb non-significantly more sensitive (McNemar OR 1.9, 95%CI 0.95–3.85); however, AS detect infestation in 12 DUs negative by DDmb Ref., reference; in the “Comparison” column, letters in parentheses indicate whether the study area was (c) or was not (nc) under chemical vector control; (nc/c) indicates that some, but not all, houses had been recently sprayed, and (nd) that no data on spraying were provided; AS, active searches by vector control staff (ASfo, using a flushing-out agent, generally a low-concentration pyrethroid solution; ASkd, using full insecticide application to ‘knock-down’ the bugs); DD, vector-detection devices (DDgn, Gómez-Núñez boxes; DDmb, ‘María’ boxes; DDsf, ‘Santa Fe’ boxes; DDb, box; DDps, paper sheet; DDp, plastic boxes; DDtb ‘tetra-brick’ recycled boxes; whenever several designs [or an undescribed one] were used, no specification is given); Rp, Rhodnius prolixus; Ti, Triatoma infestans; Ts, Triatoma sordida; Pm, Panstrongylus megistus; Rec, Rhodnius ecuadoriensis; mo, month(s); yr, year(s). In the “Setting” column, the ecoregions included in each study are given in parentheses. Discussion In the long run, Chagas disease prevention will depend on keeping households free of T. cruzi vectors [60], [116], [142]. Insecticide-based control campaigns have been extremely successful, but there is compelling evidence that persistent reinfestation of a fraction of treated households is the pattern to be expected across Latin America; reinfestation, in turn, can result in disease transmission re-emergence [18], [105], [106], [143], [144]. These well-supported findings clearly substantiate the view that long-term vector surveillance will be critical for the interruption of Chagas disease transmission [5], [7], [18], [35], [142], [145], [146]. Entomological surveillance primarily aims at detecting (then eliminating) household infestation foci; it thus allows for monitoring reinfestation trends in areas under control [5], [92], [94], [95], [147]–[151]. This is of fundamental importance for both (i) eliminating residual foci of introduced species targeted for local eradication and (ii) keeping reinfestation by native species at levels below disease transmission thresholds [73], [115], [152], [153]. We note, however, that ‘native’ vector species may be equally or more efficient than introduced ones at transmitting T. cruzi, and that even the most notorious ‘primary’ vectors, T. infestans and Rhodnius prolixus, are native (and reinfest treated households) [18], [143], [154]–[158] in their original ranges. Thus, entomological surveillance has a major role to play in most of Latin America even after introduced vector populations have been eliminated; in areas under surveillance, rapid diagnostic tests could be used to discover residual or re-emergent transmission foci [142]. But in order to attain these goals, vector detection must be as effective as possible, and the evidence we have reviewed shows that available vector-detection techniques all work far from perfectly. What would be, then, the best strategy to meet the permanent challenge of detecting reinfestation? Our appraisal yields strong support to the view that notification of suspect vectors by residents is the most sensitive among the several detection approaches tested to date – and that it is also probably the cheapest. Furthermore, the difference in performance seems to widen as vector population density declines, which is the typical situation in post-control settings. Such an austere ‘participatory’ strategy signals the minimum degree of community involvement required to effectively enhance surveillance: residents are just asked to report suspect insects found in their homes, and a response is mounted by professional staff, often related to decentralised health services [142], [154], [159], [160], to eliminate infestation when needed [18], [145], [161]. An educational/communication component tailored to the social-cultural background of the community is obviously required to stimulate notification [4], [35], [162], [163], but our review suggests that very simple interventions can be effective enough. Perhaps the main challenge here is to sustain community awareness in the face of even rarer infestation events; continuous education, a clearly defined channel for communication between residents and control agents, and an opportune response to any notification (including those involving insects other than triatomines) are probably the key to long-term success [35], [73], [152], [159], [164]–[166]. This is not to say that more sophisticated approaches would not perhaps bring further benefits to people living under risk conditions. For instance, we found that most community-based experiences in Chagas disease vector surveillance are merely utilitarian, with little or no participation of the community in the design, planning, and evaluation of interventions. Effective involvement of all stakeholders along the whole process would no doubt foster true empowerment, and this could in itself result in improved health and living standards [33], [34], [167]–[171]. Still, we underscore that, in the absence of adequate resources for comprehensive community-based programmes, stimulating vector notification by residents may suffice to boost the efficiency of entomological surveillance across highly diverse ecological and socio-economic settings. Finally, our review revealed that there is plenty of room for improvement of both methodological and reporting standards in the Chagas disease control/surveillance literature. In many cases, the results were reported incompletely and/or confusingly, sometimes precluding data extraction; in several instances, the data in the text, tables, and figures were incongruent. Indeed, just a few of the reviewed studies followed high-quality designs (e.g., with some sort of randomisation) and used sound analytical approaches, particularly in relation to the non-independence of observations; these reports tended to rely on small sample sizes and/or have limited spatial scope. Apart from the obvious need for using adequate design and analytical procedures, several guidelines for good reporting practices are readily available (e.g., the STROBE statement [172]); researchers and journal editors share the responsibility of improving the standards of published reports on Chagas disease control and prevention. Indeed, we believe that the main limitations of our review relate to the quality of the original reports, even if the breadth of our appraisal probably lightens the effects of individual study drawbacks. We did not test formally for publication bias, but deem it unlikely that any major study was overlooked; the possibility that such a bias exists should however be kept in mind when interpreting our results, particularly in relation to vector-detection devices. In an attempt to overcome possible study-level biases, we made every effort to extract and re-analyse the data in each document, without taking reported results at face value, but this does not alleviate design or data collection bias. However, we are confident that our main findings (that reinfestation by triatomines is common and widespread and that householder involvement in vector reporting enhances surveillance) are not bias-induced artefacts. We also note that our assessment focused on the initial stage of surveillance – the detection of infestation foci. The responses triggered by detection events, the monitoring of infestation trends, and the analysis and dissemination of epidemiological data are also essential components of disease surveillance [173], but their appraisal was beyond the scope of this review. Conclusions and outlook Entomological surveillance is and will remain crucial to contain Chagas disease transmission; yet, the zoonotic nature of the parasite's life cycle implies that eradication is unfeasible [1]. The enduring challenge of household reinfestation by locally native vectors can only be met by means of horizontal strategies – and these work better when the community takes on a protagonist role. Even very simple forms of participation, such as encouraging vector notification by residents, can substantially enhance the effectiveness of surveillance. Control programmes should therefore incorporate community-based approaches as a strategic asset from inception; such approaches must include a timely, professional response to every notification, and would very likely benefit from a strengthened focus on community empowerment. It must finally be emphasised that, in practice, vector detection failures are unavoidable, particularly when bug population density is low [174]. It may then be argued that infestation rates are virtually always underestimated and that, because these rates are the foremost indicator used in decision-making [175], imperfect detection can seriously misguide Chagas disease control programme management. We consequently suggest that a critical area for future research relates to the reliable estimation of vector detection probabilities. This is somewhat more difficult in the absence of a ‘gold-standard’ technique, but by no means unworkable: repeated-sampling approaches [176]–[178] readily yield detection probability estimates (with confidence intervals) that can in addition be modelled as a function of covariates – such as, for instance, alternative detection methods, different fieldwork teams, different vector species, or physically diverse ecotopes. These approaches have been successfully applied in wildlife [179] and disease ecology studies [180], [181], and can also help enhance Chagas disease vector research [182]. Supporting Information Abstract S1 Spanish and Portuguese translations of the abstract. (DOC) Click here for additional data file. Checklist S1 PRISMA checklist. (DOC) Click here for additional data file. List S1 93 documents submitted to full data extraction. (DOC) Click here for additional data file. List S2 27 documents used in partial quantitative assessments but not submitted to full data extraction. (DOC) Click here for additional data file.