Surveillance for Action: Operationalizing Private Sector Surveillance and Service Delivery across the Malaria Transmission Continuum.

Despite global recommendations that surveillance systems should capture malaria case data from both private and public sectors, the integration of private sector data into national systems remains a challenge for national malaria programs in high-burden settings. The WHO's Malaria Surveillance, Monitoring & Evaluation: A Reference Manual suggests eight general guidelines for conducting private sector surveillance. Practical operational guidance is needed to implement private sector surveillance and service delivery interventions. This commentary describes available evidence and lessons learned from the Greater Mekong subregion and sub-Saharan Africa on mapping and geolocating private providers; adding private providers to national digital registries; strengthening regulation, training, and supervision; providing feedback; and subsidizing commodities. Reporting tools should be electronic, aligned or integrated with existing national systems, and adapted to meet private sector needs. A strong enabling environment is also required, including regulatory systems that mandate private providers be registered and report into national surveillance systems. Where possible, existing systems and government personnel should be used to train, supervise, and mentor private providers. Commodities such as quality-assured artemisinin combination therapies and rapid diagnostic tests need to be available to clients at affordable prices. Finally, any parallel private sector surveillance systems need to be incorporated into the Ministry of Health systems, and the Ministry of Health needs to regularly engage with the private sector. However, the private sector contains a broad spectrum of provider types and varies across countries. Strategies need to be adapted to local contexts.

Use of a health worker-targeted smartphone app to support quality malaria RDT implementation in Busia County, Kenya: A feasibility and acceptability study.

Malaria rapid diagnostic tests (mRDTs) are an essential diagnostic tool in low-resource settings; however, administration and interpretation errors reduce their effectiveness. HealthPulse, a smartphone mRDT reader application, was developed by Audere to aid health workers in mRDT administration and interpretation, with an aim to improve the mRDT testing process and facilitate timely decision making through access to digitized results. Audere partnered with PSI and PS Kenya to conduct a pilot study in Busia County, Kenya between March and September 2021 to assess the feasibility and acceptability of HealthPulse to support malaria parasitological diagnosis by community health volunteers (CHVs) and private clinic health workers (private clinic HWs). Metadata was interpreted to assess adherence to correct use protocols and health worker perceptions of the app. Changes to mRDT implementation knowledge were measured through baseline and endline surveys. The baseline survey identified clear mRDT implementation gaps, such as few health workers correctly knowing the number of diluent drops and minimum and maximum wait times for mRDT interpretation, although health worker knowledge improved after using the app. Endline survey results showed that 99.6% of health workers found the app useful and 90.1% found the app easy to use. Process control data showed that most mRDTs (89.2%) were photographed within the recommended 30-minute time frame and that 91.4% of uploaded photos passed the app filter quality check on the first submission. During 154 encounters (3.5% of all encounters) a health worker dispensed an artemisinin-based combination therapy (ACT) to their patient even with a negative mRDT readout. Overall, study results indicated that HealthPulse holds potential as a mobile tool for use in low-resource settings, with future supportive supervision, diagnostic, and surveillance benefits. Follow-up studies will aim to more deeply understand the utility and acceptance of the HealthPulse app.

Key factors associated with malaria infection among patients seeking care through the public sector in endemic townships of Ayeyarwady Region, Myanmar.

BACKGROUND: Ayeyarwady Region in Myanmar has made significant progress towards malaria elimination, with cases decreasing from 12,312 in 2015 to 122 in 2019. As transmission declines, malaria becomes increasingly focalized both in geographic hotspots and among population groups sharing certain risk factors. Developing a thorough profile of high-risk activities associated with malaria infections is critical to ensure intervention approaches are evidence-based. METHODS: A test-negative study was conducted from September 2017 to May 2018 in Ngaputaw, Pathein and Thabaung townships in Ayeyarwady Region. Patients that presented to selected public facilities or community health volunteers with fever answered survey questions on demographic and behavioural risk factors, including exposure to malaria interventions, and were assigned to case and control groups based on the result of a malaria rapid diagnostic test. A random-effects logistic regression model adjusted for clustering at the facility level, as well as any variables along the causal pathway described by a directed acyclic graph, was used to determine odds ratios and association with malaria infections. RESULTS: A total of 119 cases and 1744 controls were recruited from 41 public facilities, with a mean age of 31.3 and 63.7% male. Higher risk groups were identified as males (aOR 1.8, 95% CI 1.2-2.9) and those with a worksite located within the forest (aOR 2.8, 95% CI 1.4-5.3), specifically working in the logging (aOR 2.7, 95% CI 1.5-4.6) and rubber plantation (aOR 3.0, 95% CI 1.4-6.8) industries. Additionally, links between forest travel and malaria were observed, with risk factors identified to be sleeping in the forest within the past month (aOR 2.6, 95% CI 1.1-6.3), and extended forest travel with durations from 3 to 14 days (aOR 8.6, 95% CI 3.5-21.4) or longer periods (aOR 8.4, 95% CI 3.2-21.6). CONCLUSION: Malaria transmission is highly focalized in Ayeyarwady, and results illustrate the need to target interventions to the most at-risk populations of working males and forest goers. It will become increasingly necessary to ensure full intervention coverage of at-risk populations active in forested areas as Myanmar moves closer to malaria elimination goals.

Factors associated with the decline of malaria in Myanmar's Ayeyarwady Region between 2013 and 2017.

The burden of malaria in Myanmar has declined rapidly in recent years; cases decreased from 333,871 in 2013 to 85,019 in 2017 (75% decrease). Decline of malaria in the Ayeyarwady Region of Myanmar reflects this trend with an 86% decrease in cases over this period. In this exploratory analysis, quantitative and qualitative information were assessed to explore potential factors responsible for the decline of malaria in Ayeyarwady. Data on malaria incidence, programmatic financing, surveillance, case management, vector control interventions, climate and ecological factors, and policies and guidelines spanning 2013 to 2017 were compiled. Poisson regression models that adjust for correlation were used to analyze the association between annual malaria case numbers with malaria intervention factors at the township level. Between 2013 and 2017, there was a decrease in mean township-level malaria incidence per 1000 from 3.03 (SD 4.59) to 0.34 (SD 0.79); this decline coincided with the implementation of the government's multi-pronged malaria elimination strategy, an increase of approximately 50.8 million USD in malaria funding nationally, and a period of deforestation in the region. Increased funding in Ayeyarwady was invested in interventions associated with the decline in caseload, and the important roles of surveillance and case management should be maintained while Myanmar works towards malaria elimination.

Strengthening surveillance systems for malaria elimination: a global landscaping of system performance, 2015-2017.

BACKGROUND: Surveillance is a core component of an effective system to support malaria elimination. Poor surveillance data will prevent countries from monitoring progress towards elimination and targeting interventions to the last remaining at-risk places. An evaluation of the performance of surveillance systems in 16 countries was conducted to identify key gaps which could be addressed to build effective systems for malaria elimination. METHODS: A standardized surveillance system landscaping was conducted between 2015 and 2017 in collaboration with governmental malaria programmes. Malaria surveillance guidelines from the World Health Organization and other technical bodies were used to identify the characteristics of an optimal surveillance system, against which systems of study countries were compared. Data collection was conducted through review of existing material and datasets, and interviews with key stakeholders, and the outcomes were summarized descriptively. Additionally, the cumulative fraction of incident infections reported through surveillance systems was estimated using surveillance data, government records, survey data, and other scientific sources. RESULTS: The landscaping identified common gaps across countries related to the lack of surveillance coverage in remote communities or in the private sector, the lack of adequate health information architecture to capture high quality case-based data, poor integration of data from other sources such as intervention information, poor visualization of generated information, and its lack of availability for making programmatic decisions. The median percentage of symptomatic cases captured by the surveillance systems in the 16 countries was estimated to be 37%, mostly driven by the lack of treatment-seeking in the public health sector (64%) or, in countries with large private sectors, the lack of integration of this sector within the surveillance system. CONCLUSIONS: The landscaping analysis undertaken provides a clear framework through which to identify multiple gaps in current malaria surveillance systems. While perfect systems are not required to eliminate malaria, closing the gaps identified will allow countries to deploy resources more efficiently, track progress, and accelerate towards malaria elimination. Since the landscaping undertaken here, several countries have addressed some of the identified gaps by improving coverage of surveillance, integrating case data with other information, and strengthening visualization and use of data.

Multinational patterns of seasonal asymmetry in human movement influence infectious disease dynamics.

Seasonal variation in human mobility is globally ubiquitous and affects the spatial spread of infectious diseases, but the ability to measure seasonality in human movement has been limited by data availability. Here, we use mobile phone data to quantify seasonal travel and directional asymmetries in Kenya, Namibia, and Pakistan, across a spectrum from rural nomadic populations to highly urbanized communities. We then model how the geographic spread of several acute pathogens with varying life histories could depend on country-wide connectivity fluctuations through the year. In all three countries, major national holidays are associated with shifts in the scope of travel. Within this broader pattern, the relative importance of particular routes also fluctuates over the course of the year, with increased travel from rural to urban communities after national holidays, for example. These changes in travel impact how fast communities are likely to be reached by an introduced pathogen.

Advances in mapping malaria for elimination: fine resolution modelling of Plasmodium falciparum incidence.

The long-term goal of the global effort to tackle malaria is national and regional elimination and eventually eradication. Fine scale multi-temporal mapping in low malaria transmission settings remains a challenge and the World Health Organisation propose use of surveillance in elimination settings. Here, we show how malaria incidence can be modelled at a fine spatial and temporal resolution from health facility data to help focus surveillance and control to population not attending health facilities. Using Namibia as a case study, we predicted the incidence of malaria, via a Bayesian spatio-temporal model, at a fine spatial resolution from parasitologically confirmed malaria cases and incorporated metrics on healthcare use as well as measures of uncertainty associated with incidence predictions. We then combined the incidence estimates with population maps to estimate clinical burdens and show the benefits of such mapping to identifying areas and seasons that can be targeted for improved surveillance and interventions. Fine spatial resolution maps produced using this approach were then used to target resources to specific local populations, and to specific months of the season. This remote targeting can be especially effective where the population distribution is sparse and further surveillance can be limited to specific local areas.

Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data.

Humans move frequently and tend to carry parasites among areas with endemic malaria and into areas where local transmission is unsustainable. Human-mediated parasite mobility can thus sustain parasite populations in areas where they would otherwise be absent. Data describing human mobility and malaria epidemiology can help classify landscapes into parasite demographic sources and sinks, ecological concepts that have parallels in malaria control discussions of transmission foci. By linking transmission to parasite flow, it is possible to stratify landscapes for malaria control and elimination, as sources are disproportionately important to the regional persistence of malaria parasites. Here, we identify putative malaria sources and sinks for pre-elimination Namibia using malaria parasite rate (PR) maps and call data records from mobile phones, using a steady-state analysis of a malaria transmission model to infer where infections most likely occurred. We also examined how the landscape of transmission and burden changed from the pre-elimination setting by comparing the location and extent of predicted pre-elimination transmission foci with modeled incidence for 2009. This comparison suggests that while transmission was spatially focal pre-elimination, the spatial distribution of cases changed as burden declined. The changing spatial distribution of burden could be due to importation, with cases focused around importation hotspots, or due to heterogeneous application of elimination effort. While this framework is an important step towards understanding progressive changes in malaria distribution and the role of subnational transmission dynamics in a policy-relevant way, future work should account for international parasite movement, utilize real time surveillance data, and relax the steady state assumption required by the presented model.

Strengthening malaria diagnosis and appropriate treatment in Namibia: a test of case management training interventions in Kavango Region.

BACKGROUND: Despite its importance in control and elimination settings, malaria diagnosis rates tend to be low in many African countries. An operational research pilot was conducted in Namibia to identify the key barriers to appropriate diagnosis of malaria in public health facilities and to evaluate the effectiveness of various training approaches in improving the uptake and adherence to rapid diagnostic tests (RDTs). METHODS: After identifying case management weaknesses through focus group discussions, training interventions were designed to address these barriers over a six-month period. The study had three intervention districts and one control within the Kavango region of Namibia where poor case management practices were observed. The interventions included an enhanced training model, clinical mentorship, and SMS reminders. Monthly data on testing and treatment were collected for the period of April to September 2012 and, for comparison, the same months during the prior year from all 52 health facilities in Kavango. The same indicators were also obtained at district level for a follow-up period of 15 months from October 2012 to December 2013 to observe whether any improvements were sustained over time. RESULTS: All intervention arms produced significant improvements in case management practices compared to the control district (all p < 0.02). Overall, districts receiving any training improved testing rates from 25% to 66% at minimum compared to the control. The enhanced training plus mentorship arm resulted in a significantly greater proportion of fevers receiving RDTs compared to the district receiving enhanced training alone, increasing from 27% to over 90% at endline. No ACT was prescribed to untested patients after caregivers received mentorship or SMS reminders. These improvements were all sustained over the 15-month follow-up. CONCLUSIONS: These changes show a reversal of improper case management practices over the six-month study period and demonstrate that implementing simple training interventions can have a significant, sustainable impact on the uptake of and adherence to malaria RDTs. Findings from this work have already informed Namibia's roll out of a more robust case management training programme. The approaches used in Namibia may be applicable to other resource-constrained countries, providing practical guidance on sustainable approaches to febrile illness management.

Integrating rapid risk mapping and mobile phone call record data for strategic malaria elimination planning.

BACKGROUND: As successful malaria control programmes re-orientate towards elimination, the identification of transmission foci, targeting of attack measures to high-risk areas and management of importation risk become high priorities. When resources are limited and transmission is varying seasonally, approaches that can rapidly prioritize areas for surveillance and control can be valuable, and the most appropriate attack measure for a particular location is likely to differ depending on whether it exports or imports malaria infections. METHODS/RESULTS: Here, using the example of Namibia, a method for targeting of interventions using surveillance data, satellite imagery, and mobile phone call records to support elimination planning is described. One year of aggregated movement patterns for over a million people across Namibia are analyzed, and linked with case-based risk maps built on satellite imagery. By combining case-data and movement, the way human population movements connect transmission risk areas is demonstrated. Communities that were strongly connected by relatively higher levels of movement were then identified, and net export and import of travellers and infection risks by region were quantified. These maps can aid the design of targeted interventions to maximally reduce the number of cases exported to other regions while employing appropriate interventions to manage risk in places that import them. CONCLUSIONS: The approaches presented can be rapidly updated and used to identify where active surveillance for both local and imported cases should be increased, which regions would benefit from coordinating efforts, and how spatially progressive elimination plans can be designed. With improvements in surveillance systems linked to improved diagnosis of malaria, detailed satellite imagery being readily available and mobile phone usage data continually being collected by network providers, the potential exists to make operational use of such valuable, complimentary and contemporary datasets on an ongoing basis in infectious disease control and elimination.

The association between height and prostate cancer grade in the Early Stage Prostate Cancer Cohort Study.

OBJECTIVE: We examined the relationship between height and prostate cancer grade. METHODS: The Early Stage Prostate Cancer Cohort Study is an observational cohort of 1,037 men diagnosed with early-stage prostate cancer, T(0-3)N(x)M(0). High-grade prostate cancer was defined as a biopsy Gleason score ≥ 7 (4 + 3). Logistic regression models were created to calculate odds ratios (OR) and 95% confidence intervals (CI) for the cross-sectional relationship between height and prostate cancer grade in the overall cohort and subpopulations. RESULTS: We identified 939 participants with a biopsy Gleason score. High-grade prostate cancer was diagnosed in 138 participants. Overall, participants in the highest quartile of height were more than twice as likely to have a Gleason score ≥ 7 (4 + 3) than participants in the lowest quartile of height, OR 2.14 (95% CI 1.11, 4.14), after multivariate adjustment. Participants in the highest quartile of height were more likely to be diagnosed with high-grade prostate cancer than participants in the lowest quartile of height among participants who were black, OR 8.00 (95% CI 1.99, 32.18), and participants who had diabetes mellitus, OR 5.09 (95% CI 1.30, 19.98). CONCLUSIONS: Height is associated with increased risk of high-grade prostate cancer overall and perhaps among certain subpopulations.

A route for fructose utilization by Escherichia coli involving the fucose regulon.

Fructose can be taken up by Escherichia coli via a variety of membrane-spanning proteins that recognize sugars with the 3,4,5-d-arabino-hexose configuration. Here, we describe a mutant that is devoid of those proteins but takes up fructose via the FucP carrier normally used for the transport of alpha-L-fucose; this implies that the fructose is taken up in the alpha- or beta-fructopyranose form. For growth, the assimilated fructose is sequentially phosphorylated by ATP and (i) manno(fructo)kinase, to form fructose 6-phosphate, and (ii) phosphofructokinase, to form fructose 1,6-bisphosphate, which is a member of central routes of glycolysis and gluconeogenesis. The mutation that confers on the organism the ability to take up fructose via the fucose regulon was located as a deletion of the fucA gene with consequent induction of the proton-linked fucose transporter, FucP.