Background Eliminating malaria and preventing re-establishment of malaria transmission in border areas requires universal coverage of malaria surveillance and a rapid response to any threats (i.e. malaria cues) of re-establishing transmission. Main text Strategy 1: Intensive interventions within 2.5 km-wide perimeter along the border to prevent border-spill malaria. The area within 2.5 km along the international border is the travel radius of anopheline mosquitoes. Comprehensive interventions should include: (1) proactive and passive case detection, (2) intensive vector surveillance, (3) evidence-based vector control, and (4) evidence-based preventative treatment with anti-malarial drugs. Strategy 2: Community-based malaria detection and screening of migrants and travellers in frontier townships. Un-permitted travellers cross borders frequently and present in frontier townships. Maintenance of intensified malaria surveillance should include: (1) passive malaria detection in the township hospitals, (2) seek assistance from villager leaders and health workers to monitor cross border travellers, and refer febrile patients to the township hospitals and (3) the county’s Centre for Disease Control and Prevention maintain regular proactive case detection. Strategy 3: Universal coverage of malaria surveillance to detect malaria cues. Passive detection should be consolidated into the normal health service. Health services personnel should remain vigilant to ensure universal coverage of malaria detection and react promptly to any malaria cues. Strategy + 1: Strong collaborative support with neighbouring countries. Based on the agreement between the two countries, integrated control strategies should be carried out to reduce malaria burden for both countries. There should be a clear focus on the border areas between neighbouring countries. Conclusion The 3 + 1 strategy is an experience summary of border malaria control and elimination, and then contributed to malaria elimination in Yunnan’s border areas, China. Nevertheless, Yunnan still has remaining challenges of re-establishment of malaria transmission in the border areas, and the 3 + 1 strategy should still be carried out.

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Background Eradication of infectious disease is the sanctified public health and sustainable development goal around the world. Main body Three antimalarial barriers were developed to control imported malarial cases, and an effective surveillance strategy known as the “1–3–7 approach” was developed to eliminate malaria from the Chinese population. From 2011 to 2019, 5254 confirmed malaria cases were reported and treated in Yunnan Province, China. Among them, 4566 cases were imported from other countries, and 688 cases were indigenous from 2011 to 2016. Since 2017, no new local malarial case has been reported in China. Thus, malaria has been completely eliminated in Yunnan Province. However, malaria is detected in overseas travellers on a regular basis, such as visitors from neighbouring Myanmar. Conclusion Hence, the strategies should be further strengthened to maintain a robust public health infrastructure for disease surveillance and vector control programs in border areas. Such programs should be supported technically and financially by the government to avert the possibility of a malarial resurgence in Yunnan Province. Graphic Abstract

The heterogeneity and complexity of malaria involves political and natural environments, socioeconomic development, cross-border movement, and vector biology; factors that cannot be changed in a short time. This study aimed to assess the impact of economic growth and cross-border movement, toward elimination of malaria in Yunnan Province during its pre-elimination phase. Malaria data during 2011-2016 were extracted from 18 counties of Yunnan and from 7 villages, 11 displaced person camps of the Kachin Special Region II of Myanmar. Data of per-capita gross domestic product (GDP) were obtained from Yunnan Bureau of Statistics. Data were analyzed and mapped to determine spatiotemporal heterogeneity at county and village levels. There were a total 2,117 malaria cases with 85.2% imported cases; most imported cases came from Myanmar (78.5%). Along the demarcation line, malaria incidence rates in villages/camps in Myanmar were significantly higher than those of the neighboring villages in China. The spatial and temporal trends suggested that increasing per-capita GDP may have an indirect effect on the reduction of malaria cases when observed at macro level; however, malaria persists owing to complex, multi-faceted factors including poverty at individual level and cross-border movement of the workforce. In moving toward malaria elimination, despite economic growth, cooperative efforts with neighboring countries are critical to interrupt local transmission and prevent reintroduction of malaria via imported cases. Cross-border workers should be educated in preventive measures through effective behavior change communication, and investment is needed in active surveillance systems and novel diagnostic and treatment services during the elimination phase.

. In moving toward malaria elimination, finer scale malaria risk maps are required to identify hotspots for implementing surveillance–response activities, allocating resources, and preparing health facilities based on the needs and necessities at each specific area. This study aimed to demonstrate the use of multi-criteria decision analysis (MCDA) in conjunction with geographic information systems (GISs) to create a spatial model and risk maps by integrating satellite remote-sensing and malaria surveillance data from 18 counties of Yunnan Province along the China–Myanmar border. The MCDA composite and annual models and risk maps were created from the consensus among the experts who have been working and know situations in the study areas. The experts identified and provided relative factor weights for nine socioeconomic and disease ecology factors as a weighted linear combination model of the following: ([Forest coverage × 0.041] + [Cropland × 0.086] + [Water body × 0.175] + [Elevation × 0.297] + [Human population density × 0.043] + [Imported case × 0.258] + [Distance to road × 0.030] + [Distance to health facility × 0.033] + [Urbanization × 0.036]). The expert-based model had a good prediction capacity with a high area under curve. The study has demonstrated the novel integrated use of spatial MCDA which combines multiple environmental factors in estimating disease risk by using decision rules derived from existing knowledge or hypothesized understanding of the risk factors via diverse quantitative and qualitative criteria using both data-driven and qualitative indicators from the experts. The model and fine MCDA risk map developed in this study could assist in focusing the elimination efforts in the specifically identified locations with high risks.