Tick (Acari: Ixodoidea) fauna and zoogeographic division of Jiangxi Province, China.

Tick fauna and zoogeographic distribution of Jiangxi Province remain largely unknown due to the lack of data on distribution, occurrence, and host associations of ticks. Considering this, we collected 1,817 individual samples from natural hosts, humans, and vegetation in 18 counties/districts throughout Jiangxi Province, China, from 2015 to 2021. These 1,817 individuals were found to 13 tick species, 4 genera, and 1 family. In addition, the tick sample data from 8 sampling localities (counties and districts) reported in previous studies were also included in our data. A total of 4,021 individuals, including our sample collection and the previously reported data, were assigned to at least 18 species, 6 genera, and 2 families. One newly recorded species Dermacentor sp. (near D. steini Schulze) was found; three misidentified species (Ixodes acuminatus, Haemaphysalis spinigera, and Haemaphysalis verticalis) reported previously were deleted; and one misidentified species Dermacentor auratus Supino was revised as Dermacentor steini Schulze. In addition, we divided the tick fauna in Jiangxi Province into 5 zoogeographic areas and assigned the 18 tick species collected from 26 localities to these 5 zoogeographic areas. To summarize, our findings provide valuable information on the distribution, tick-host associations, and zoogeographic division of ticks in Jiangxi Province, China. Their molecular characterizations, phylogenetic relationships, and tick-borne pathogens that they may transmit should be further explored.

A framework for assessing local transmission risk of imported malaria cases.

BACKGROUND: A key issue in achieving and sustaining malaria elimination is the need to prevent local transmission arising from imported cases of malaria. The likelihood of this occurring depends on a range of local factors, and these can be used to allocate resources to contain transmission. Therefore, a risk assessment and management strategy is required to identify risk indexes for malaria transmission when imported cases occur. These risks also need to be quantified and combined to give a weighted risk index score. This can then be used to allocate the resources to each administrative region to prevent transmission according to the degree of risk. METHODS: A list of potential risk indexes were generated from a literature review, expert consultation and panel discussion. These were initially classified into 4 first-level indexes including infection source, transmitting conditions, population vulnerability and control capacity. Each of these was then expanded into more detailed second-level indexes. The Delphi method was then used to obtain expert opinion to review and revise these risk indexes over two consecutive rounds to quantify agreement among experts as to their level of importance. Risk indexes were included in the final Transmission Risk Framework if they achieved a weighted importance score ≥ 4. The Analytic Hierarchy Process was then used to calculate the weight allocated to each of the final risk indexes. This was then used to create an assessment framework that can be used to evaluate local transmission risk in different areas. RESULTS: Two rounds of Delphi consultation were conducted. Twenty-three experts were used at each round with 100% recovery rate of participant questionnaires. The coordination coefficients (W) for the two rounds of Delphi consultation were 0.341 and 0.423, respectively (P < 0.05). Three first-level indexes and 13 second-level indexes were identified. The Analytic Hierarchy Process was performed to calculate the weight of the indexes. For the first-level indexes, infection source, transmitting conditions, and control capacity, the index weight was 0.5396, 0.2970 and 0.1634 respectively. For the three top second-level indexes, number of imported malaria cases, Anopheles species, and awareness of timely medical visit of patient, the index weight was 0.3382, 0.2475, and 0.1509 respectively. CONCLUSIONS: An indexed system of transmission risk assessment for imported malaria was established using the Delphi method and the Analytic Hierarchy Process. This was assessed to be an objective and practical tool for assessing transmission risk from imported cases of malaria into China.