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Epidemic surveillance in a low resource setting: lessons from an evaluation of the Solomon Islands syndromic surveillance system, 2017.

ABSTRACT: BACKGROUND:Solomon Islands is one of the least developed countries in the world. Recognising that timely detection of outbreaks is needed to enable early and effective response to disease outbreaks, the Solomon Islands government introduced a simple syndromic surveillance system in 2011. We conducted the first evaluation of the system and the first exploration of a national experience within the broader multi-country Pacific Syndromic Surveillance System to determine if it is meeting its objectives and to identify opportunities for improvement. METHODS:We used a multi-method approach involving retrospective data collection and statistical analysis, modelling, qualitative research and observational methods. RESULTS:We found that the system was well accepted, highly relied upon and designed to account for contextual limitations. We found the syndromic algorithm used to identify outbreaks was moderately sensitive, detecting 11.8% (IQR: 6.3-25.0%), 21.3% (IQR: 10.3-36.8%), 27.5% (IQR: 12.8-52.3%) and 40.5% (IQR: 13.5-65.7%) of outbreaks that caused small, moderate, large and very large increases in case presentations to health facilities, respectively. The false alert rate was 10.8% (IQR: 4.8-24.5%). Rural coverage of the system was poor. Limited workforce, surveillance resourcing and other 'upstream' health system factors constrained performance. CONCLUSIONS:The system has made a significant contribution to public health security in Solomon Islands, but remains insufficiently sensitive to detect small-moderate sized outbreaks and hence should not be relied upon as a stand-alone surveillance strategy. Rather, the system should sit within a complementary suite of early warning surveillance activities including event-based, in-patient- and laboratory-based surveillance methods. Future investments need to find a balance between actions to address the technical and systems issues that constrain performance while maintaining simplicity and hence sustainability.

SUBMITTER: Craig AT

PROVIDER: S-EPMC6302379 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Project description:BackgroundRecent arboviral disease outbreaks highlight the value a better understanding of the spread of disease-carrying mosquitoes across spatial-temporal scales can provide. Traditional surveillance tools are limited by jurisdictional boundaries, workforce constraints, logistics, and cost; factors that in low- and middle-income countries often conspire to undermine public health protection efforts. To overcome these, we undertake a pilot study designed to explore if citizen science provides a feasible strategy for arboviral vector surveillance in small developing Pacific island contexts.MethodsWe recruited, trained, and equipped community volunteers to trap and type mosquitos within their household settings, and to report count data to a central authority by short-message-service. Mosquito catches were independently assessed to measure participants' mosquito identification accuracy. Other data were collected to measure the frequency and stability of reporting, and volunteers' experiences.ResultsParticipants collected data for 78.3% of the study period, and agreement between the volunteer citizen scientists' and the reviewing entomologist's mosquito identification was 94%. Opportunity to contribute to a project of social benefit, the chance to learn new skills, and the frequency of engagement with project staff were prime motivators for participation. Unstable electricity supply (required to run the trap's fan), insufficient personal finances (to buy electricity and phone credit), and inconvenience were identified as barriers to sustained participation.ConclusionsWhile there are challenges to address, our findings suggest that citizen science offers an opportunity to overcome the human resource constraints that conspire to limit health authorities' capacity to monitor arboviral vectors across populations. We note that the success of citizen science-based surveillance is dependent on the appropriate selection of equipment and participants, and the quality of engagement and support provided.

Project description:BackgroundSuccessful reduction of malaria transmission to very low levels has made Isabel Province, Solomon Islands, a target for early elimination by 2014. High malaria transmission in neighbouring provinces and the potential for local asymptomatic infections to cause malaria resurgence highlights the need for sub-national tailoring of surveillance interventions. This study contributes to a situational analysis of malaria in Isabel Province to inform an appropriate surveillance intervention.MethodsA mixed method study was carried out in Isabel Province in late 2009 and early 2010. The quantitative component was a population-based prevalence survey of 8,554 people from 129 villages, which were selected using a spatially stratified sampling approach to achieve uniform geographical coverage of populated areas. Diagnosis was initially based on Giemsa-stained blood slides followed by molecular analysis using polymerase chain reaction (PCR). Local perceptions and practices related to management of fever and treatment-seeking that would impact a surveillance intervention were also explored using qualitative research methods.ResultsApproximately 33% (8,554/26,221) of the population of Isabel Province participated in the survey. Only one subject was found to be infected with Plasmodium falciparum (Pf) (96 parasites/?L) using Giemsa-stained blood films, giving a prevalence of 0.01%. PCR analysis detected a further 13 cases, giving an estimated malaria prevalence of 0.51%. There was a wide geographical distribution of infected subjects. None reported having travelled outside Isabel Province in the previous three months suggesting low-level indigenous malaria transmission. The qualitative findings provide warning signs that the current community vigilance approach to surveillance will not be sufficient to achieve elimination. In addition, fever severity is being used by individuals as an indicator for malaria and a trigger for timely treatment-seeking and case reporting. In light of the finding of a low prevalence of parasitaemia, the current surveillance system may not be able to detect and prevent malaria resurgence.ConclusionAn adaption to the malERA surveillance framework is proposed and recommendations made for a tailored provincial-level surveillance intervention, which will be essential to achieve elimination, and to maintain this status while the rest of the country catches up.

Project description:BackgroundA high-resolution surveillance-response system has been developed within a geographic information system (GIS) to support malaria elimination in the Pacific. This paper examines the application of a GIS-based spatial decision support system (SDSS) to automatically locate and map the distribution of confirmed malaria cases, rapidly classify active transmission foci, and guide targeted responses in elimination zones.MethodsCustomized SDSS-based surveillance-response systems were developed in the three elimination provinces of Isabel and Temotu, Solomon Islands and Tafea, Vanuatu. Confirmed malaria cases were reported to provincial malaria offices upon diagnosis and updated into the respective SDSS as part of routine operations throughout 2011. Cases were automatically mapped by household within the SDSS using existing geographical reconnaissance (GR) data. GIS queries were integrated into the SDSS-framework to automatically classify and map transmission foci based on the spatiotemporal distribution of cases, highlight current areas of interest (AOI) regions to conduct foci-specific targeted response, and extract supporting household and population data. GIS simulations were run to detect AOIs triggered throughout 2011 in each elimination province and conduct a sensitivity analysis to calculate the proportion of positive cases, households and population highlighted in AOI regions of a varying geographic radius.ResultsA total of 183 confirmed cases were reported and mapped using the SDSS throughout 2011 and used to describe transmission within a target population of 90,354. Automatic AOI regions were also generated within each provincial SDSS identifying geographic areas to conduct response. 82.5% of confirmed cases were automatically geo-referenced and mapped at the household level, with 100% of remaining cases geo-referenced at a village level. Data from the AOI analysis indicated different stages of progress in each province, highlighting operational implications with regards to strategies for implementing surveillance-response in consideration of the spatiotemporal nature of cases as well as logistical and financial constraints of the respective programmes.ConclusionsGeospatial systems developed to guide Pacific Island malaria elimination demonstrate the application of a high resolution SDSS-based approach to support key elements of surveillance-response including understanding epidemiological variation within target areas, implementing appropriate foci-specific targeted response, and consideration of logistical constraints and costs.

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Epidemic surveillance in a low resource setting: lessons from an evaluation of the Solomon Islands syndromic surveillance system, 2017.

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