Background Remaining Plasmodium falciparum cases in Cambodia are concentrated in forested border areas and in remote populations who are hard to reach through passive case detection. A key approach to reach these populations is active case detection by mobile malaria workers (MMWs). However, this is operationally challenging because of changing movement patterns of the target population moving into less accessible areas. From January 2018 to December 2020, a tailored package of active case detection approaches was implemented in forested border areas of three provinces in north-eastern Cambodia to reach remote populations and support the elimination of falciparum malaria. Methods Key elements of this project were to tailor approaches to local populations, use responsive monitoring systems, maintain operational flexibility, build strong relationships with local communities, and implement close supervision practices. MMWs were recruited from local communities. Proactive case detection approaches included mobile malaria posts positioned at frequented locations around and within forests, and locally informed outreach activities targeting more remote locations. Reactive case detection was conducted among co-travellers of confirmed cases. Testing for malaria was conducted independent of fever symptoms. Routine monitoring of programmatic data informed tactical adaptations, while supervision exercises ensured service quality. Results Despite operational challenges, service delivery sites were able to maintain consistently high testing rates throughout the implementation period, with each of 45 sites testing a monthly average of 64 (SD 6) people in 2020. In 2020, project MMWs detected only 32 P. falciparum cases. Over the project period, the P. falciparum/P. vivax ratio steadily inversed. Including data from neighbouring health centres and village malaria workers, 45% (80,988/180,732) of all people tested and 39% (1280/3243) of P. falciparum cases detected in the area can be attributed to project MMWs. Remaining challenges of the last elimination phase include maintaining intensified elimination efforts, addressing the issue of detecting low parasitaemia cases and shifting focus to P. vivax malaria. Conclusions Reaching remote populations through active case detection should remain a key strategy to eliminate P. falciparum malaria. This case study presented a successful approach combining tailored proactive and reactive strategies that could be transferred to similar settings in other areas of the Greater Mekong Subregion.

Illusory face detection tasks can be used to study the neural correlates of top-down influences on face perception. In a typical functional magnetic resonance imaging (fMRI) study design, subjects are presented with pure noise images, but are told that half of the stimuli contain a face. The illusory face perception network is assessed by comparing blood oxygenation level dependent (BOLD) responses to images in which a face has been detected against BOLD activity related to images in which no face has been detected. In the present study, we highlight the existence of strong interindividual differences of BOLD activation patterns associated with illusory face perception. In the core system of face perception, 4 of 9 subjects had highly significant (p<0.05, corrected for multiple comparisons) activity in the bilateral occipital face area (OFA) and fusiform face area (FFA). In contrast, 5 of 9 subjects did not show any activity in these regions, even at statistical thresholds as liberal as p = 0.05, uncorrected. At the group level, this variability is reflected by non-significant activity in all regions of the core system. We argue that these differences might be related to individual differences in task execution: only some participants really detected faces in the noise images, while the other subjects simply responded in the desired way. This has several implications for future studies on illusory face detection. First, future studies should not only analyze results at the group level, but also for single subjects. Second, subjects should be explicitly queried after the fMRI experiment about whether they really detected faces or not. Third, if possible, not only the overt response of the subject, but also additional parameters that might indicate the perception of a noise stimulus as face should be collected (e.g., behavioral classification images).

Background Manual assessment of respiratory rate (RR) in children is unreliable, but remains the main method to diagnose pneumonia in low-resource settings. While automated RR counters offer a potential solution, there is currently no gold standard to validate these diagnostic aids. A video-based reference tool is proposed that allows users to annotate breaths and distortions including movement periods, allowing the exclusion of distortions from the computation of RR measures similar to how new diagnostic aids account for distortions automatically. This study evaluated the interrater agreement and acceptability of the new reference tool. Methods Annotations were based on previously recorded reference videos of children under five years old with cough and/or difficulty breathing (n = 50). Five randomly selected medical experts from a panel of ten annotated each video. RR measures (breaths per minute, bpm) were computed as the number of annotated certain breaths divided by the length of calm periods after removing annotated distorted periods. Results Reviewers showed good interrater agreement on continuous RR {standard error of measurement (SEM) [4.8 (95%CI 4.4–5.3)]} and substantial agreement on classification of fast breathing (Fleiss kappa, κ 0.71). Agreement was lowest in the youngest age group [&lt; 2 months: SEM 6.2 (5.4–7.4) bpm, κ 0.48; 2–11 months: 4.7 (4.0–5.8) bpm, κ 0.84; 12–59 months: 2.6 (2.2–3.1) bpm, κ 0.8]. Reviewers found the functionalities of the tool helpful in annotating breaths, but remained uncertain about the validity of their annotations. Conclusions Before the new tool can be considered a reference standard for RR assessments, interrater agreement in children younger than 2 months must be improved.

Adaptive surveillance systems are essential for national programmes to achieve their malaria elimination goals. Core principles of surveillance systems including accurate diagnosis and reporting of malaria cases, integration of health data across administrative levels and the need to link data to a response are well defined by international guidelines. Nevertheless, while the requirements of surveillance systems along the transmission continuum are clearly documented, the operationalization remains challenging for national programmes. Firstly, because the multi-level increase of surveillance efforts demanding real-time and case-based data as well as the capacity of the health force to trigger locally customized responses, is resource intensive and requires substantial investment. Secondly, because there is a gap in international alignment on best tools and practices on how to operationally implement these requirements. Recently, several initiatives have started to address this gap in international coordination, aiming to establish the operational guidance for elimination programmes to successfully implement adaptive surveillance systems.

Background: Remaining Plasmodium falciparum cases in Cambodia are concentrated in forested border areas and in remote populations who are hard to reach through passive case detection. A key approach to reach these populations is active case detection by mobile malaria workers (MMWs). However, this is operationally challenging because of changing movement patterns of the target population moving into less accessible areas. From 2018 to 2020, a tailored package of active case detection approaches was implemented in forested border areas of three provinces in north-eastern Cambodia to reach remote populations and support the elimination of P. falciparum malaria.Approach: Key elements of this project were to tailor approaches to local populations, use responsive monitoring systems, maintain operational flexibility, build strong relationships with local communities, and implement close supervision practices. MMWs were recruited from local communities. Proactive case detection approaches included mobile malaria posts positioned at frequented locations around and within forests, and locally informed outreach activities targeting more remote locations. Reactive case detection was conducted among co-travellers of confirmed cases. Tests were conducted independent of fever symptoms. Routine monitoring informed tactical adaptations, while supervision exercises ensured service quality. Results: Despite operational challenges, between January 2018 and June 2020, service delivery sites were able to maintain consistently high testing rates, with each site testing a monthly average of > 60 people in 2020. Over the project period, the P. falciparum/ P. vivax ratio has steadily inversed. In 2020, MMWs detected only 22 P. falciparum cases with constant testing rates. Including data from neighbouring health facilities and village malaria workers, 52% of all people tested and 40% of P. falciparum cases detected in the area can be attributed to MMWs.Remaining challenges: Maintaining intensified elimination efforts, addressing the issue of detecting low parasitemia cases and shifting focus to P. vivax malaria challenge the last phase of malaria elimination.Conclusions: Reaching remote populations through active case detection should remain a key strategy to eliminate P. falciparum malaria. We have presented a successful approach combining tailored proactive and reactive strategies that could be transferred to similar settings in other areas of the Greater Mekong Subregion.