Characterizing Types of Human Mobility to Inform Differential and Targeted Malaria Elimination Strategies in Northeast Cambodia

Human population movements currently challenge malaria elimination in low transmission foci in the Greater Mekong Subregion. Using a mixed-methods design, combining ethnography (n?=?410 interviews), malariometric data (n?=?4996) and population surveys (n?=?824 indigenous populations; n?=?704 Khmer migrants) malaria vulnerability among different types of mobile populations was researched in the remote province of Ratanakiri, Cambodia. Different structural types of human mobility were identified, showing differential risk and vulnerability. Among local indigenous populations, access to malaria testing and treatment through the VMW-system and LLIN coverage was high but control strategies failed to account for forest farmers’ prolonged stays at forest farms/fields (61% during rainy season), increasing their exposure (p?=?0.002). The Khmer migrants, with low acquired immunity, active on plantations and mines, represented a fundamentally different group not reached by LLIN-distribution campaigns since they were largely unregistered (79%) and unaware of the local VMW-system (95%) due to poor social integration. Khmer migrants therefore require control strategies including active detection, registration and immediate access to malaria prevention and control tools from which they are currently excluded. In conclusion, different types of mobility require different malaria elimination strategies. Targeting mobility without an in-depth understanding of malaria risk in each group challenges further progress towards elimination

Diagnosis and management of malaria by rural community health providers in the Lao People's Democratic Republic (Laos).

We assessed the knowledge of malaria diagnosis and management by community health providers in rural Vientiane and Savannakhet Provinces, Lao PDR. Sixty health providers (17 pharmacy owners/drug sellers and 43 village health volunteers) were interviewed. All diagnosed malaria using symptoms and signs only; 14% were aware of >2 criteria for the diagnosis of severe malaria. Although chloroquine and quinine, the then recommended Lao national policy for uncomplicated malaria treatment, were the most common antimalarials prescribed - 65% gave incorrect doses and 70% did not know the side effects. Although not recommended by the then national policy, 27% of the health providers used combinations of antimalarials as they considered monotherapy ineffective. This study strongly suggests that further training of Lao rural health providers in malaria diagnosis and management is needed to improve the quality of health services in areas remote from district hospitals

Diagnosis and management of malaria by rural community health providers in the Lao People's Democratic Republic (Laos).

We assessed the knowledge of malaria diagnosis and management by community health providers in rural Vientiane and Savannakhet Provinces, Lao PDR. Sixty health providers (17 pharmacy owners/drug sellers and 43 village health volunteers) were interviewed. All diagnosed malaria using symptoms and signs only; 14% were aware of >2 criteria for the diagnosis of severe malaria. Although chloroquine and quinine, the then recommended Lao national policy for uncomplicated malaria treatment, were the most common antimalarials prescribed - 65% gave incorrect doses and 70% did not know the side effects. Although not recommended by the then national policy, 27% of the health providers used combinations of antimalarials as they considered monotherapy ineffective. This study strongly suggests that further training of Lao rural health providers in malaria diagnosis and management is needed to improve the quality of health services in areas remote from district hospitals

Accounting for aetiology: can regional surveillance data alongside host biomarker-guided antibiotic therapy improve treatment of febrile illness in remote settings?

Background: Across Southeast Asia, declining malaria incidence poses a challenge for healthcare providers, in how best to manage the vast majority of patients with febrile illnesses who have a negative malaria test. In rural regions, where the majority of the population reside, empirical treatment guidelines derived from central urban hospitals are often of limited relevance. In these settings, health workers with limited training deliver care, often without any laboratory diagnostic support. In this paper, we model the impact of point-of-care C-reactive protein testing to inform the decision to prescribe antibiotics and regional surveillance data to inform antibiotic selection, and then simulate the subsequent impact on mortality from febrile illnesses, rooted in the real-world context of rural Savannakhet province, southern Laos. Methods: Our model simulates 100 scenarios with varying quarterly incidence of six key pathogens known to be prevalent in rural Laos. In the simulations, community health workers either prescribe antibiotics in-line with current practice as documented in health facilities in rural Laos, or with the aid of the two interventions. We provide cost-effectiveness estimates for each strategy alone and then for an integrated approach using both interventions. Results: We find that each strategy is predicted to be highly cost-effective, and that the combined approach is predicted to result in the biggest reduction in mortality (averting a predicted 510 deaths per year in rural Savannakhet, a 28% reduction compared to standard practice) and is highly cost-effective, with an incremental cost-effectiveness ratio of just $66 per disability-adjusted life year averted. Conclusions: Substantial seasonal variation in the predicted optimal empirical antibiotic treatment for febrile illness highlights the benefits of up-to-date information on regional causes of fever. In this modelling analysis, an integrated system incorporating point-of-care host biomarker testing and regional surveillance data appears highly cost-effective, and may warrant piloting in a real-life setting.</br

Accounting for aetiology: can regional surveillance data alongside host biomarker-guided antibiotic therapy improve treatment of febrile illness in remote settings?

Background: Across Southeast Asia, declining malaria incidence poses a challenge for healthcare providers, in how best to manage the vast majority of patients with febrile illnesses who have a negative malaria test. In rural regions, where the majority of the population reside, empirical treatment guidelines derived from central urban hospitals are often of limited relevance. In these settings, health workers with limited training deliver care, often without any laboratory diagnostic support. In this paper, we model the impact of point-of-care C-reactive protein testing to inform the decision to prescribe antibiotics and regional surveillance data to inform antibiotic selection, and then simulate the subsequent impact on mortality from febrile illnesses, rooted in the real-world context of rural Savannakhet province, southern Laos. Methods: Our model simulates 100 scenarios with varying quarterly incidence of six key pathogens known to be prevalent in rural Laos. In the simulations, community health workers either prescribe antibiotics in-line with current practice as documented in health facilities in rural Laos, or with the aid of the two interventions. We provide cost-effectiveness estimates for each strategy alone and then for an integrated approach using both interventions. Results: We find that each strategy is predicted to be highly cost-effective, and that the combined approach is predicted to result in the biggest reduction in mortality (averting a predicted 510 deaths per year in rural Savannakhet, a 28% reduction compared to standard practice) and is highly cost-effective, with an incremental cost-effectiveness ratio of just $66 per disability-adjusted life year averted. Conclusions: Substantial seasonal variation in the predicted optimal empirical antibiotic treatment for febrile illness highlights the benefits of up-to-date information on regional causes of fever. In this modelling analysis, an integrated system incorporating point-of-care host biomarker testing and regional surveillance data appears highly cost-effective, and may warrant piloting in a real-life setting.</br

YLubell/SEA-CTN: surveillance-poct

Background: Across Southeast Asia, declining malaria incidence poses a challenge for healthcare providers, in how best to manage the vast majority of patients with febrile illnesses who have a negative malaria test. In rural regions, where the majority of the population reside, empirical treatment guidelines derived from central urban hospitals are often of limited relevance. In these settings, relatively untrained health workers deliver care, often without any laboratory diagnostic support. In this paper, our aim was to model the impact on mortality from febrile illness of using point-of-care C-reactive protein testing to inform the decision to prescribe antibiotics and regional surveillance data to inform antibiotic selection, rooted in the real-world context of rural Savannakhet province, southern Laos. Methods: Our model simulates 100 scenarios with varying quarterly incidence of six key pathogens known to be prevalent in rural Laos. In the simulations, community health workers either prescribe antibiotics in-line with current practice as documented in health facilities in rural Laos, or with the aid of the two interventions. We provide cost-effectiveness estimates for each strategy alone and then for an integrated approach using both interventions. Results: We find that each strategy alone is predicted to be highly cost-effective, and that the combined approach is predicted to result in the biggest reduction in mortality (averting a predicted 510 deaths per year in rural Savannakhet, a 28% reduction compared to standard practice) and is highly cost-effective, with an incremental cost-effectiveness ratio of just $66 per disability-adjusted life year averted. Conclusions: Substantial seasonal variation in the predicted optimal empirical antibiotic treatment for febrile illness highlights the benefits of up-to-date information on regional causes of fever. In this modelling analysis, an integrated system incorporating point-of-care host biomarker testing and regional surveillance data appears highly cost-effective, and may warrant piloting in a real-life setting