Published on in Vol 7, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19034, first published .
Early Detection of Dengue Fever Outbreaks Using a Surveillance App (Mozzify): Cross-sectional Mixed Methods Usability Study

Early Detection of Dengue Fever Outbreaks Using a Surveillance App (Mozzify): Cross-sectional Mixed Methods Usability Study

Early Detection of Dengue Fever Outbreaks Using a Surveillance App (Mozzify): Cross-sectional Mixed Methods Usability Study

Von Ralph Dane Marquez Herbuela   1, 2 , PhD ;   Tomonori Karita   3 , PhD ;   Thaddeus Marzo Carvajal   1, 4 , PhD ;   Howell Tsai Ho   5 , PhD ;   John Michael Olea Lorena   6 , PhD ;   Rachele Arce Regalado   7 , MA ;   Girly Dirilo Sobrepeña   8 , MD ;   Kozo Watanabe   1, 4 , PhD

1 Center for Marine Environmental Studies, Ehime University, Matsuyama, Japan

2 Department of Civil and Environmental Engineering, Graduate School of Science and Engineering, Ehime University, Matsuyama, Japan

3 Department of Special Needs Education, Graduate School of Education, Ehime University, Matsuyama, Japan

4 Biological Control Research Unit, Center for Natural Science and Environmental Research, De La Salle University, Manila, Philippines

5 College of Arts, Sciences and Education, Trinity University of Asia, Quezon City, Philippines

6 St. Luke’s College of Nursing, Trinity University of Asia, Quezon City, Philippines

7 Guidance Counseling and Testing Department, University of Santo Tomas–Angelicum College, Quezon City, Philippines

8 Pediatrics Department, Novaliches District Hospital, Quezon City, Philippines

Corresponding Author: