Table 1 Study characteristics and summary of the 11 prediction models reported in 10 included the studies

1

Schöder and Schmidt 2008

Lower Saxony, Germany

Routine

surveillance data and literature record

Malaria was eliminated in 1964

Exisitng Vector:

Anopheles atroparvus

Mathematical method: Basic reproduction number (R₀)

Temperature (average air temperature)

1.Mosquito density;

2.The number of bites per person per day;

3.The length of the gonotrophic cycle;

4.Proportion of female mosquitoes with developing parasites after taking an infected blood meal;

5.Daily survival probability of an adult female mosquito;

6.Period of parasite development in the adult female mosquito in days

–

–

The immunity of local people

Not mentioned

Not mentioned

2

Lindsay et al. 2010

The United Kingdom

Routine

surveillance data

Malaria was eliminated in 1963

Exisitng Vector

Anopheles atroparvus

Mathematical method: Basic reproduction number (R₀)

Temperature (average air temperature)

1.Mosquito density;

2.The number of bites per person per day;

3.The length of the gonotrophic cycle;

4.Proportion of female mosquitoes with developing parasites after taking an infected blood meal;

5.Daily survival probability of an adult female mosquito;

6.Period of parasite development in the adult female mosquito in days

Number of imported cases

–

The immunity of local people

Not mentioned

External validation was performed by comparing potential distribution of malaria between 1961–1990 and 1859–1864

Statistical method: Logistic regression

1.Temperature (the mean temperature of the warmest month; the mean temperature of the coldest month);

2.Index of wetness (an index of wetness which is a measure of potential evaporation in

relation to rainfall)

–

Number of imported cases

–

Population density

Not mentioned

Not mentioned

3

Sainz-Elipe et al. 2010

The Ebro Delta

in the province of Tarragona, Spain

Routine

surveillance data and cross-sectional survey

Malaria was eliminated in 1964

Exisitng Vector:

Anopheles atroparvus

Mathematical method: Gradient Model Risk Index

1.Temperature (mean maximum temperature, mean minimum temperature, mean environmental temperature);

2.Rainfall;

3.Relative humidity;

4.Potential evapotranspiration;

5.Wind speed;

6.Vapor pressure;

7.Global radiation;

8.Terrain characterization

Population dynamics of A. atroparvus

–

–

Not mentioned

Not mentioned

4

Romi et al. 2012

Maremma plain,central Italy

Routine

surveillance data and cross-sectional survey

Malaria was eliminated in 1970

Exisitng Vector:

Anopheles maculipennis

Mathematical method: Receptivity of the area-Susceptibility of the vector-Vulnerability of the territory

1.Rainfall;

2.Potential evapotranspiration

1.Species, blood meal source and age population structure of mosquito;

2.Abundance of larvae/adult mosquito;

3.The length of the possible transmission season for P. vivax and P. falciparum;

4.The vectorial capacity and host feeding preference of An. labranchiae;

5.Vectorial capacity of An. labranchiae in the site where the

species is most abundant;

6.The possibility of vector may feed on gametocyte carriers

–

–

–

Not mentioned

Not mentioned

5

Sudre et al. 2013

Greece

Routine

surveillance data

Malaria was eliminated in 2012

Exisitng Vector

Anopheles sacharovi; Anopheles superpictus

Statistical method: Bootstrap model

1.Temperature;

2.Vegetation seasonal variations;

3.Altitude;

4.Land-cover categories

–

–

–

Population density

Sensitivity:0.98,

Specificity:0.98

Not mentioned

6

Pergantas et al. 2017

8 municipalities of the Prefecture of central Greece

From the European Environment and Epidemiology Network data repository

Malaria was eliminated in 2012

Exisitng Vector

Anopheles sacharovi; Anopheles superpictus

Mathematical method: Basic reproduction number (R₀)

Temperature

1.The ratio of mosquitoes/humans;

2.The biting rate(proportion of mosquitoes that feed on humans each day);

3.The mosquito latent period (the number of days from infection to infectiousness);

4.Mosquito death rate per day;

5.Probability a bite produces infection to a human;

6.Probability a mosquito becomes infected after biting an infected human

1.Migrant;

2.Distances of migrant population from the larvae areas

–

The immunity of local people

Not mentioned

Not mentioned

7

Kamana et al. 2022

China

Routine

surveillance data

Malaria was eliminated in 2021

Exisitng Vector: Anopheles sinensis, Anopheles minimus, Anopheles dirus,

Anopheles lesteri

Machine learning method: LSTM neural networks

1.Temperature (average maximum and minimum temperature);

2.Rainfall;

3.Relative humidity

–

–

–

Average prediction

accuracy of LSTMSeq2Seq model = 87.3%

Not mentioned

8

Lan et al. 2022

China

Cross-sectional survey

Malaria was eliminated in 2021

Exisitng Vector

Anopheles sinensis, Anopheles minimus, Anopheles dirus,

Anopheles lesteri

Delphi method

1.Temperature;

2.Rainfall;

3.Altitude

1.Type of vector;

2.Density of vector;

3.Biting rate;

4.Susceptibility of vectors to plasmodium

5. Sensitivity of vectors to insecticides

1.Number of imported case;

2.Companion of imported cases

1.Awareness of malaria control knowledge;

2.Multi-sectoral joint prevention and control

mechanism;

3.Implementation of ' 1–3-7 malaria surveillance and response strategy

4.Vector surveillance

5.Diagnostic capability

6.Proportion of initial diagnosis of malaria by

medical institutions;

7.Proportion of fever patients receiving blood tests

1.Time of malaria cases imported to China;

2.Malaria prevalence in the overseas country

Not mentioned

Not mentioned

9

Li et al. 2022

Changsha, Hunan Province, China

Routine

surveillance data

Malaria was eliminated in 2021

Exisitng Vector:

Anopheles sinensis, Anopheles minimus, Anopheles dirus,

Anopheles lesteri

Delphi method

–

Anopheles mosquito-borne malaria risk index (Anopheles species)

1.Number of imported cases;

2.Type of imported malaria cases

1.Implementation of ' 1–3-7 malaria surveillance and response strategy

2.Capability of blood testing (laboratory diagnosis rate);

3. Standardized treatment rate;

4.Treatment capacity of medical institutions

Funding for malaria prevention and control

Not mentioned

Not mentioned

10

Liu et al. 2023

China

Cross-sectional survey

Malaria was eliminated in 2021

Exisitng Vector: Anopheles sinensis, Anopheles minimus, Anopheles dirus,

Anopheles lesteri

Delphi method

1.Temperature;

2.Rainfall;

3.Altitude

4. Relative humidity

5. Season

6. Anopheles breeding environment

7. Livestock breeding

1.Local Anopheles species

2.Anopheles density

3.Sensitivity of vectors to insecticides

4.Vectorial capacity

5.Susceptibility of vectors to plasmodium

1.Number of migrants

2.Awareness of malaria control knowledge among migrants

3.Mosquito bites of imported personnel in the overseas country

4.Occupation in the overseas country

5.Residence time in the overseas country

6.Residency in the overseas country (e.g. urban/rural/estate)

7.Number of imported cases

1.Diagnostic and discovery capability of customs district

2.Awareness of health-seeking of imported personnel

3.Diagnostic and treatment capacity of health workers

4.The number of malaria control staff

5.stockpiling anti-malarial drugs

6.Implementation of ' 1–3-7 malaria surveillance and response strategy

7.Vector surveillance

8.Multi-sectoral joint prevention and control

mechanism

1.Malaria surveillence capacity in countries where malaria has been imported

2.Accessibility of antimalarial drugs in the overseas country

3.Governments ' attention and financial support

4.The geography and malaria situation in countries where malaria has been imported (e.g. whether the country is cross-border or not)

5.The number of years after malaria elimination

6.Plasmodium species in the overseas country

Not mentioned

Not mentioned